From 9926ea12da5a849e20b942dac33f86887816e715 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?=E3=82=AD=E3=83=A7=E3=83=BB=E3=83=AA=E3=83=BC=E3=82=B7?= =?UTF-8?q?=E3=83=A5=E3=83=B3?= Date: Mon, 16 Jun 2025 13:21:29 +0900 Subject: [PATCH 01/16] Add SAM2 --- .../AiliaImageSegmentation2Sample.cs | 568 ++++ .../AiliaImageSegmentation2Sample.cs.meta | 11 + .../ImageSegmentation2Sample.unity | 554 ++++ .../ImageSegmentation2Sample.unity.meta | 7 + .../ImageSegmentation2/SampleImage.meta | 8 + .../ImageSegmentation2/SampleImage/couple.jpg | Bin 0 -> 20290 bytes .../SampleImage/couple.jpg.meta | 152 ++ .../ImageSegmentation2/SampleImage/girl.png | Bin 0 -> 234498 bytes .../SampleImage/girl.png.meta | 152 ++ .../ImageSegmentation2/SampleImage/hair.jpg | Bin 0 -> 25632 bytes .../SampleImage/hair.jpg.meta | 152 ++ .../ImageSegmentation2/SampleImage/hair2.jpg | Bin 0 -> 54460 bytes .../SampleImage/hair2.jpg.meta | 152 ++ .../ImageSegmentation2/SampleImage/modnet.jpg | Bin 0 -> 48615 bytes .../SampleImage/modnet.jpg.meta | 152 ++ .../ImageSegmentation2/SampleImage/road.png | Bin 0 -> 92863 bytes .../SampleImage/road.png.meta | 152 ++ .../ImageSegmentation2/SampleImage/truck.jpg | Bin 0 -> 271475 bytes .../SampleImage/truck.jpg.meta | 159 ++ .../SegmentAnything2Model.cs | 2274 +++++++++++++++++ .../SegmentAnything2Model.cs.meta | 11 + .../ImageSegmentation2/Segmentation2Model.cs | 391 +++ .../Segmentation2Model.cs.meta | 11 + 23 files changed, 4906 insertions(+) create mode 100644 Assets/AXIP/AILIA-MODELS/ImageSegmentation2/AiliaImageSegmentation2Sample.cs create mode 100644 Assets/AXIP/AILIA-MODELS/ImageSegmentation2/AiliaImageSegmentation2Sample.cs.meta create mode 100644 Assets/AXIP/AILIA-MODELS/ImageSegmentation2/ImageSegmentation2Sample.unity create mode 100644 Assets/AXIP/AILIA-MODELS/ImageSegmentation2/ImageSegmentation2Sample.unity.meta create mode 100644 Assets/AXIP/AILIA-MODELS/ImageSegmentation2/SampleImage.meta create mode 100644 Assets/AXIP/AILIA-MODELS/ImageSegmentation2/SampleImage/couple.jpg create mode 100644 Assets/AXIP/AILIA-MODELS/ImageSegmentation2/SampleImage/couple.jpg.meta create mode 100644 Assets/AXIP/AILIA-MODELS/ImageSegmentation2/SampleImage/girl.png create mode 100644 Assets/AXIP/AILIA-MODELS/ImageSegmentation2/SampleImage/girl.png.meta create mode 100644 Assets/AXIP/AILIA-MODELS/ImageSegmentation2/SampleImage/hair.jpg create mode 100644 Assets/AXIP/AILIA-MODELS/ImageSegmentation2/SampleImage/hair.jpg.meta create mode 100644 Assets/AXIP/AILIA-MODELS/ImageSegmentation2/SampleImage/hair2.jpg create mode 100644 Assets/AXIP/AILIA-MODELS/ImageSegmentation2/SampleImage/hair2.jpg.meta create mode 100644 Assets/AXIP/AILIA-MODELS/ImageSegmentation2/SampleImage/modnet.jpg create mode 100644 Assets/AXIP/AILIA-MODELS/ImageSegmentation2/SampleImage/modnet.jpg.meta create mode 100644 Assets/AXIP/AILIA-MODELS/ImageSegmentation2/SampleImage/road.png create mode 100644 Assets/AXIP/AILIA-MODELS/ImageSegmentation2/SampleImage/road.png.meta create mode 100644 Assets/AXIP/AILIA-MODELS/ImageSegmentation2/SampleImage/truck.jpg create mode 100644 Assets/AXIP/AILIA-MODELS/ImageSegmentation2/SampleImage/truck.jpg.meta create mode 100644 Assets/AXIP/AILIA-MODELS/ImageSegmentation2/SegmentAnything2Model.cs create mode 100644 Assets/AXIP/AILIA-MODELS/ImageSegmentation2/SegmentAnything2Model.cs.meta create mode 100644 Assets/AXIP/AILIA-MODELS/ImageSegmentation2/Segmentation2Model.cs create mode 100644 Assets/AXIP/AILIA-MODELS/ImageSegmentation2/Segmentation2Model.cs.meta diff --git a/Assets/AXIP/AILIA-MODELS/ImageSegmentation2/AiliaImageSegmentation2Sample.cs b/Assets/AXIP/AILIA-MODELS/ImageSegmentation2/AiliaImageSegmentation2Sample.cs new file mode 100644 index 00000000..9789ce76 --- /dev/null +++ b/Assets/AXIP/AILIA-MODELS/ImageSegmentation2/AiliaImageSegmentation2Sample.cs @@ -0,0 +1,568 @@ +/* AILIA Unity Plugin Segmentation Sample */ +/* Copyright 2018-2022 AXELL CORPORATION */ + +using System; +using System.Collections.Generic; +using UnityEngine; +using UnityEngine.UI; + +using ailia; + +namespace ailiaSDK +{ + // Model list + public enum ImageSegmentaion2Models + { + // HRNetV2_W18_Small_v2, + // HRNetV2_W18_Small_v1, + // HRNetV2_W48, + // hair_segmentation, + // pspnet_hair_segmentation, + // deeplabv3, + // u2net, + // modnet, + image_encoder_hiera_l + } + + public class AiliaImageSegmentation2Sample : MonoBehaviour + { + // Settings + public ImageSegmentaion2Models ImageSegmentaion2Models = + ImageSegmentaion2Models.image_encoder_hiera_l; + public bool gpu_mode = false; + public GameObject UICanvas = null; + public bool camera_mode = true; + public int camera_id = 0; + + // Result + RawImage raw_image = null; + Text label_text = null; + Text mode_text = null; + private bool oneshot = true; + + // AILIA + private AiliaCamera ailia_camera = new AiliaCamera(); + + // Input source + AiliaImageSource AiliaImageSource; + public Texture2D image_source_hrnet = null; + public Texture2D image_source_hair_segmentation = null; + public Texture2D image_source_pspnet_hair_segmentation = null; + public Texture2D image_source_deeplabv3 = null; + public Texture2D image_source_u2net = null; + public Texture2D image_source_modnet = null; + public Texture2D image_source_sam1 = null; + + // Pre-and-Post processing Shader + Material blendMaterial; + int mainTexId; + int blendTexId; + int blendFlagId; + int mainVFlipId; + int blendVFlipId; + + // Model input and output + + Texture2D labelTexture; + Texture2D originalTexture; + Vector2 rawImageSize; + + // Segment Anything Model + private Segmentation2Model seg2Model; + private SegmentAnything2Model sam2Model; + private bool isDraggingForBox = false; + private Rect boxRect = new(); + + bool modelPrepared = false; + bool modelAllocated = false; + string envName = ""; + + async void Start() + { + Debug.Log("Start"); + AiliaLicense.CheckAndDownloadLicense(); + UISetup(); + + AiliaImageSource = gameObject.GetComponent(); + + // for Rendering + blendMaterial = new Material(Shader.Find("Ailia/AlphaBlending2Tex")); + mainTexId = Shader.PropertyToID("_MainTex"); + blendTexId = Shader.PropertyToID("_BlendTex"); + blendFlagId = Shader.PropertyToID("blendFlag"); + mainVFlipId = Shader.PropertyToID("mainVFlip"); + blendVFlipId = Shader.PropertyToID("blendVFlip"); + raw_image.material = blendMaterial; + + rawImageSize = raw_image.rectTransform.sizeDelta; + + // for Processing + AiliaInit(); + + // for Camera + if (camera_mode) + { + bool crop_square = false; + ailia_camera.CreateCamera(camera_id, crop_square); + } + } + + void AiliaInit() + { + // Create Ailia + CreateAiliaNet(ImageSegmentaion2Models, gpu_mode); + + // Load sample image + LoadImage(ImageSegmentaion2Models, AiliaImageSource); + } + + void UISetup() + { + Debug.Assert(UICanvas != null, "UICanvas is null"); + + label_text = UICanvas.transform.Find("LabelText").GetComponent(); + mode_text = UICanvas.transform.Find("ModeLabel").GetComponent(); + raw_image = UICanvas.transform.Find("RawImage").GetComponent(); + raw_image.gameObject.SetActive(false); + + if (ImageSegmentaion2Models == ImageSegmentaion2Models.image_encoder_hiera_l) + { + mode_text.text = + "ailia Image Segmentation 2\n" + + "Left/Right click: positive/negative point\n" + + "Middle click: drag to define border box\n" + + "Space key down to reset"; + } + else + { + mode_text.text = "ailia Image Segmentation 2"; + } + } + + Color32[] VerticalFlip(Color32[] inputImage, int InputWidth, int InputHeight) + { + Color32[] outputImage = new Color32[InputWidth * InputHeight]; + for (int y = 0; y < InputHeight; y++) + { + for (int x = 0; x < InputWidth; x++) + { + outputImage[(InputHeight - 1 - y) * InputWidth + x] = inputImage[ + y * InputWidth + x + ]; + } + } + return outputImage; + } + + void Update() + { + HandleClick(Input.GetMouseButton(0), Input.GetMouseButton(1), Input.GetMouseButton(2)); + + if (AiliaImageSource == null || !AiliaImageSource.IsPrepared || !modelPrepared) + { + return; + } + if (modelPrepared && !modelAllocated) + { + if (ImageSegmentaion2Models != ImageSegmentaion2Models.image_encoder_hiera_l) + { + seg2Model.AllocateInputAndOutputTensor( + ImageSegmentaion2Models, + AiliaImageSource.Width, + AiliaImageSource.Height + ); + } + modelAllocated = true; + } + if (camera_mode && !ailia_camera.IsEnable()) + { + return; + } + + // When space key down, draw original image + if (Input.GetKey(KeyCode.Space)) + { + if (ImageSegmentaion2Models == ImageSegmentaion2Models.image_encoder_hiera_l) + { + sam2Model.ResetClickPoint(); + boxRect = new(); + oneshot = true; + } + blendMaterial.SetFloat(blendFlagId, 0); + } + else + { + blendMaterial.SetFloat(blendFlagId, 1); + } + + // Only one shot processing for image mode + if (!oneshot && !camera_mode) + { + return; + } + + // Make input data + long start_time = DateTime.UtcNow.Ticks / TimeSpan.TicksPerMillisecond; + Color32[] inputImage = null; + int inputImageWidth = 0; + int inputImageHeight = 0; + if (camera_mode) + { + inputImageWidth = ailia_camera.GetWidth(); + inputImageHeight = ailia_camera.GetHeight(); + inputImage = ailia_camera.GetPixels32(); // Bottom2Top format + inputImage = VerticalFlip(inputImage, inputImageWidth, inputImageHeight); // Top2Bottom format + } + else + { + bool convert_to_top2bottom = true; + inputImageWidth = AiliaImageSource.Width; + inputImageHeight = AiliaImageSource.Height; + Rect rect = new Rect(0, 0, inputImageWidth, inputImageHeight); + inputImage = AiliaImageSource.GetPixels32(rect, convert_to_top2bottom); // Top2Bottom format + } + + long end_time = DateTime.UtcNow.Ticks / TimeSpan.TicksPerMillisecond; + + // Predict + long start_time2 = DateTime.UtcNow.Ticks / TimeSpan.TicksPerMillisecond; + + bool result = false; + if (ImageSegmentaion2Models == ImageSegmentaion2Models.image_encoder_hiera_l) + { + if (!sam2Model.EmbeddingExist()) + { + if (sam2Model.GetClickPoints(0).Length == 0) + { + sam2Model.AddClickPoint(inputImageWidth / 4, inputImageHeight / 4 + 30); + } + } + if (camera_mode || !sam2Model.EmbeddingExist()) + { + sam2Model.ProcessEmbedding(inputImage, inputImageWidth, inputImageHeight); + } + sam2Model.ProcessMask(inputImage, inputImageWidth, inputImageHeight); + result = sam2Model.success; + } + else + { + result = seg2Model.ProcessFrame( + ImageSegmentaion2Models, + inputImage, + inputImageWidth, + inputImageHeight + ); + } + + if (!result) + { + oneshot = false; + return; + } + + // convert result to image + Color32[] outputImage; + int outputWidth, + outputHeight; + if (ImageSegmentaion2Models == ImageSegmentaion2Models.image_encoder_hiera_l) + { + outputImage = sam2Model.visualizedResult.GetPixels32(); + outputWidth = sam2Model.visualizedResult.width; + outputHeight = sam2Model.visualizedResult.height; + } + else + { + (outputImage, outputWidth, outputHeight) = seg2Model.PostProcesss( + ImageSegmentaion2Models, + inputImageWidth, + inputImageHeight + ); + } + + long end_time2 = DateTime.UtcNow.Ticks / TimeSpan.TicksPerMillisecond; + + if (label_text != null) + { + label_text.text = + ((end_time - start_time) + (end_time2 - start_time2)).ToString() + + "ms\n" + + envName; + } + + // for viewer + if (originalTexture == null) + { + originalTexture = new Texture2D( + outputWidth, + outputHeight, + TextureFormat.RGBA32, + false + ); + } + if (labelTexture == null) + { + labelTexture = new Texture2D( + outputWidth, + outputHeight, + TextureFormat.RGBA32, + false + ); + } + originalTexture.SetPixels32(inputImage); + originalTexture.Apply(); + raw_image.texture = originalTexture; + blendMaterial.SetTexture(mainTexId, originalTexture); + + labelTexture.SetPixels32(outputImage); + labelTexture.Apply(); + blendMaterial.SetTexture(blendTexId, labelTexture); + + blendMaterial.SetFloat(mainVFlipId, 1); //originalTexture is Top2Bottom + blendMaterial.SetFloat(blendVFlipId, 1); //outputImage is Top2Bottom + + float rawImageRatio = rawImageSize.x / rawImageSize.y; + float ratio = inputImageWidth / (float)inputImageHeight; + raw_image.rectTransform.sizeDelta = new Vector2( + ratio / rawImageRatio * rawImageSize.x, + rawImageSize.y + ); + + raw_image.gameObject.SetActive(true); + + oneshot = false; + } + + // Download models and Create ailiaModel + void CreateAiliaNet(ImageSegmentaion2Models modelType, bool gpu_mode = true) + { + AiliaDownload ailia_download = new AiliaDownload(); + ailia_download.DownloaderProgressPanel = UICanvas.transform + .Find("DownloaderProgressPanel") + .gameObject; + List urlList = null; + + if (ImageSegmentaion2Models == ImageSegmentaion2Models.image_encoder_hiera_l) + { + sam2Model = new SegmentAnything2Model(); + urlList = sam2Model.GetModelURLs(ImageSegmentaion2Models); + } + else + { + seg2Model = new Segmentation2Model(); + urlList = seg2Model.GetModelURLs(ImageSegmentaion2Models); + } + + StartCoroutine( + ailia_download.DownloadWithProgressFromURL( + urlList, + () => + { + if (ImageSegmentaion2Models == ImageSegmentaion2Models.image_encoder_hiera_l) + { + modelPrepared = sam2Model.InitializeModels( + ImageSegmentaion2Models, + gpu_mode + ); + envName = sam2Model.EnvironmentName(); + } + else + { + modelPrepared = seg2Model.InitializeModels( + ImageSegmentaion2Models, + gpu_mode + ); + envName = seg2Model.EnvironmentName(); + } + } + ) + ); + } + + void LoadImage( + ImageSegmentaion2Models ImageSegmentaion2Models, + AiliaImageSource ailiaImageSource + ) + { + switch (ImageSegmentaion2Models) + { + // case ImageSegmentaion2Models.HRNetV2_W18_Small_v2: + // case ImageSegmentaion2Models.HRNetV2_W18_Small_v1: + // case ImageSegmentaion2Models.HRNetV2_W48: + // ailiaImageSource.CreateSource(image_source_hrnet); + // break; + // case ImageSegmentaion2Models.hair_segmentation: + // ailiaImageSource.CreateSource(image_source_hair_segmentation); + // break; + // case ImageSegmentaion2Models.pspnet_hair_segmentation: + // ailiaImageSource.CreateSource(image_source_pspnet_hair_segmentation); + // break; + // case ImageSegmentaion2Models.deeplabv3: + // ailiaImageSource.CreateSource(image_source_deeplabv3); + // break; + // case ImageSegmentaion2Models.u2net: + // ailiaImageSource.CreateSource(image_source_u2net); + // break; + // case ImageSegmentaion2Models.modnet: + // ailiaImageSource.CreateSource(image_source_modnet); + // break; + case ImageSegmentaion2Models.image_encoder_hiera_l: + ailiaImageSource.CreateSource(image_source_sam1); + break; + } + } + + void HandleClick(bool leftClick, bool rightClick, bool middleClick) + { + if (!raw_image.isActiveAndEnabled || raw_image.texture == null) + { + return; + } + + Vector3[] corners = new Vector3[4]; + raw_image.rectTransform.GetWorldCorners(corners); + + Rect rawImageRect = new Rect( + corners[0].x, + Screen.height - corners[2].y, + corners[2].x - corners[0].x, + corners[2].y - corners[0].y + ); + + Vector2 mousePos = new Vector2(Input.mousePosition.x, Input.mousePosition.y); + + float widthRatio = raw_image.texture.width / rawImageRect.width; + float heightRatio = raw_image.texture.height / rawImageRect.height; + + int x = Mathf.Clamp( + Mathf.RoundToInt((mousePos.x - rawImageRect.x) * widthRatio), + 0, + raw_image.texture.width - 1 + ); + int y = + raw_image.texture.height + - 1 + - Mathf.Clamp( + Mathf.RoundToInt((mousePos.y - rawImageRect.y) * heightRatio), + 0, + raw_image.texture.height - 1 + ); + + if (rawImageRect.Contains(mousePos)) + { + if (leftClick || rightClick) + { + sam2Model?.AddClickPoint(x, y, rightClick); + oneshot = true; + + Debug.Log($"Click registered at: {x}, {y}"); + } + + if (middleClick && !isDraggingForBox) + { + isDraggingForBox = true; + boxRect.xMin = x; + boxRect.yMin = y; + } + } + + if (!middleClick && isDraggingForBox) + { + isDraggingForBox = false; + + float firstX = boxRect.xMin; + float firstY = boxRect.yMin; + + boxRect.xMin = Math.Min(firstX, x); + boxRect.yMin = Math.Min(firstY, y); + boxRect.xMax = Math.Max(firstX, x); + boxRect.yMax = Math.Max(firstY, y); + + sam2Model.SetBoxCoords(boxRect); + oneshot = true; + } + } + + private void OnGUI() + { + if (!raw_image.isActiveAndEnabled || raw_image.texture == null) + { + return; + } + + if ((boxRect.width > 0 && boxRect.height > 0) || isDraggingForBox) + { + Vector3[] corners = new Vector3[4]; + raw_image.rectTransform.GetWorldCorners(corners); + + Rect rawImageRect = new Rect( + corners[0].x, + Screen.height - corners[2].y, + corners[2].x - corners[0].x, + corners[2].y - corners[0].y + ); + + float widthRatio = raw_image.texture.width / rawImageRect.width; + float heightRatio = raw_image.texture.height / rawImageRect.height; + + int xMin = (int)(boxRect.xMin / widthRatio + rawImageRect.x); + int yMin = (int)(boxRect.yMin / heightRatio + rawImageRect.y); + int xMax = ( + (int)( + isDraggingForBox + ? Input.mousePosition.x + : (boxRect.xMax / widthRatio + rawImageRect.x) + ) + ); + int yMax = ( + (int)( + isDraggingForBox + ? (Screen.height - Input.mousePosition.y) + : (boxRect.yMax / heightRatio + rawImageRect.y) + ) + ); + + float thickness = 2; + Rect lineArea = new Rect(); + lineArea.xMin = xMin; + lineArea.yMin = yMin; + lineArea.xMax = xMax; + lineArea.yMax = yMax; + + lineArea.y = yMin - thickness; //Bottom + lineArea.height = thickness; //Top line + GUI.DrawTexture(lineArea, Texture2D.whiteTexture); + + lineArea.y = yMax - thickness; //Bottom + GUI.DrawTexture(lineArea, Texture2D.whiteTexture); + + lineArea.height = yMin - yMax; + lineArea.width = thickness; //Left + GUI.DrawTexture(lineArea, Texture2D.whiteTexture); + lineArea.x = xMax - thickness; //Right + GUI.DrawTexture(lineArea, Texture2D.whiteTexture); + } + } + + void OnApplicationQuit() + { + DestroyAiliaDetector(); + } + + void OnDestroy() + { + DestroyAiliaDetector(); + } + + void DestroyAiliaDetector() + { + if (sam2Model != null) + { + sam2Model.Destroy(); + } + if (seg2Model != null) + { + seg2Model.Destroy(); + } + } + } +} diff --git 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forceMaximumCompressionQuality_BC6H_BC7: 0 + - serializedVersion: 3 + buildTarget: Android + maxTextureSize: 2048 + resizeAlgorithm: 0 + textureFormat: -1 + textureCompression: 1 + compressionQuality: 50 + crunchedCompression: 0 + allowsAlphaSplitting: 0 + overridden: 0 + androidETC2FallbackOverride: 0 + forceMaximumCompressionQuality_BC6H_BC7: 0 + - serializedVersion: 3 + buildTarget: iPhone + maxTextureSize: 2048 + resizeAlgorithm: 0 + textureFormat: -1 + textureCompression: 1 + compressionQuality: 50 + crunchedCompression: 0 + allowsAlphaSplitting: 0 + overridden: 0 + androidETC2FallbackOverride: 0 + forceMaximumCompressionQuality_BC6H_BC7: 0 + - serializedVersion: 3 + buildTarget: WebGL + maxTextureSize: 2048 + resizeAlgorithm: 0 + textureFormat: -1 + textureCompression: 1 + compressionQuality: 50 + crunchedCompression: 0 + allowsAlphaSplitting: 0 + overridden: 0 + androidETC2FallbackOverride: 0 + forceMaximumCompressionQuality_BC6H_BC7: 0 + spriteSheet: + serializedVersion: 2 + sprites: [] + outline: [] + physicsShape: [] + bones: [] + spriteID: + internalID: 0 + vertices: [] + indices: + edges: [] + weights: [] + secondaryTextures: [] + nameFileIdTable: {} + spritePackingTag: + pSDRemoveMatte: 0 + pSDShowRemoveMatteOption: 0 + userData: + assetBundleName: + assetBundleVariant: diff --git a/Assets/AXIP/AILIA-MODELS/ImageSegmentation2/SegmentAnything2Model.cs b/Assets/AXIP/AILIA-MODELS/ImageSegmentation2/SegmentAnything2Model.cs new file mode 100644 index 00000000..f62760c9 --- /dev/null +++ b/Assets/AXIP/AILIA-MODELS/ImageSegmentation2/SegmentAnything2Model.cs @@ -0,0 +1,2274 @@ +/* AILIA Unity Plugin Segment Anything Sample */ +/* Copyright 2025 AXELL CORPORATION and ax Inc. */ + +using ailia; +using ailiaSDK; +using System; +using System.Collections; +using System.Collections.Generic; +using System.IO; +using System.Linq; +using System.Runtime.CompilerServices; +using System.Text; +using System.Threading; +using System.Threading.Tasks; +using UnityEngine; + +public class SegmentAnything2Model +{ + // Ailia models + private const string encoderWeightPath = "image_encoder_hiera_l.onnx"; + private const string encoderProtoPath = "image_encoder_hiera_l.onnx.prototxt"; + private const string decoderWeightPath = "mask_decoder_hiera_l.onnx"; + private const string decoderProtoPath = "mask_decoder_hiera_l.onnx.prototxt"; + + // private const string memAttentionWeightPath = "memory_attention_hiera_l.opt.onnx"; + // private const string memAttentionProtoPath = "memory_attention_hiera_l.opt.onnx.prototxt"; + // private const string encoderMemWeightPath = "memory_encoder_hiera_l.onnx"; + // private const string encoderMemProtoPath = "memory_encoder_hiera_l.onnx.prototxt"; + private const string promptWeightPath = "prompt_encoder_hiera_l.onnx"; + private const string promptProtoPath = "prompt_encoder_hiera_l.onnx.prototxt"; + + // private const string mlpWeightPath = "mlp_hiera_l.onnx"; + // private const string mlpProtoPath = "mlp_hiera_l.onnx.prototxt"; + + private List clickPoints = new(); + private List clickPointLabels = new(); + private Rect boxCoords = new(); + private bool addBoxCoords => boxCoords.width > 0 && boxCoords.height > 0; + private int targetSize = 1024; + private ailia.AiliaModel encoder; + private ailia.AiliaModel decoder; + private ailia.AiliaModel memAttention; + private ailia.AiliaModel encoderMem; + private ailia.AiliaModel prompt; + private ailia.AiliaModel mlp; + + public bool modelsInitialized { get; private set; } = false; + public bool isProcessing { get; private set; } = false; + public bool success { get; private set; } = false; + private bool gpuMode = false; + private bool showClickPoints = true; + + // Normalization constants (ImageNet) + private readonly float[] Mean = { 0.485f, 0.456f, 0.406f }; + private readonly float[] Std = { 0.229f, 0.224f, 0.225f }; + + // For async cancellation + private CancellationTokenSource cancellationTokenSource; + private bool isQuitting = false; + + // Visualization-related fields + public Texture2D visualizedResult { get; private set; } + private readonly Color32 MaskColor = new Color32(255, 0, 0, 255); + private bool saveFrame = false; + private float[] encoderOutput = null; + private float[][] highResFeats = null; + private BackboneOutputs backboneData; + private System.Random _rng = new System.Random(); + + public void SetBoxCoords(Rect box) + { + boxCoords = box; + + Debug.Log($"boxCoords set to {box.xMin},{box.yMin} {box.xMax},{box.yMax}"); + } + + public void AddClickPoint(int x, int y, bool negativePoint = false) + { + clickPoints.Add(new Vector2Int(x, y)); + clickPointLabels.Add(!negativePoint); + } + + public void ResetClickPoint() + { + clickPoints = new(); + clickPointLabels = new(); + boxCoords = new(); + } + + public List GetModelURLs(ImageSegmentaion2Models modelType) + { + List modelDownloadURLs = new List(); + string serverFolderName = "segment-anything-2"; + + modelDownloadURLs.Add( + new ModelDownloadURL() { folder_path = serverFolderName, file_name = encoderWeightPath } + ); + modelDownloadURLs.Add( + new ModelDownloadURL() { folder_path = serverFolderName, file_name = encoderProtoPath } + ); + modelDownloadURLs.Add( + new ModelDownloadURL() { folder_path = serverFolderName, file_name = decoderWeightPath } + ); + modelDownloadURLs.Add( + new ModelDownloadURL() { folder_path = serverFolderName, file_name = decoderProtoPath } + ); + // modelDownloadURLs.Add( + // new ModelDownloadURL() { folder_path = serverFolderName, file_name = memAttentionWeightPath } + // ); + // modelDownloadURLs.Add( + // new ModelDownloadURL() { folder_path = serverFolderName, file_name = memAttentionProtoPath } + // ); + // modelDownloadURLs.Add( + // new ModelDownloadURL() { folder_path = serverFolderName, file_name = encoderMemWeightPath } + // ); + // modelDownloadURLs.Add( + // new ModelDownloadURL() { folder_path = serverFolderName, file_name = encoderMemProtoPath } + // ); + modelDownloadURLs.Add( + new ModelDownloadURL() { folder_path = serverFolderName, file_name = promptWeightPath } + ); + modelDownloadURLs.Add( + new ModelDownloadURL() { folder_path = serverFolderName, file_name = promptProtoPath } + ); + // modelDownloadURLs.Add( + // new ModelDownloadURL() { folder_path = serverFolderName, file_name = mlpWeightPath } + // ); + // modelDownloadURLs.Add( + // new ModelDownloadURL() { folder_path = serverFolderName, file_name = mlpProtoPath } + // ); + + return modelDownloadURLs; + } + + // Initialize Ailia models + public bool InitializeModels(ImageSegmentaion2Models modelType, bool gpuMode) + { + if (modelsInitialized) + return true; + + try + { + string encPath = System.IO.Path.Combine( + Application.temporaryCachePath, + encoderWeightPath + ); + string encProtoPath = System.IO.Path.Combine( + Application.temporaryCachePath, + encoderProtoPath + ); + string decPath = System.IO.Path.Combine( + Application.temporaryCachePath, + decoderWeightPath + ); + string decProtoPath = System.IO.Path.Combine( + Application.temporaryCachePath, + decoderProtoPath + ); + // string memAttPath = System.IO.Path.Combine( + // Application.temporaryCachePath, + // memAttentionWeightPath + // ); + // string memAttProtoPath = System.IO.Path.Combine( + // Application.temporaryCachePath, + // memAttentionProtoPath + // ); + // string encMemPath = System.IO.Path.Combine( + // Application.temporaryCachePath, + // encoderMemWeightPath + // ); + // string encMemProtoPath = System.IO.Path.Combine( + // Application.temporaryCachePath, + // encoderMemProtoPath + // ); + string pmtPath = System.IO.Path.Combine( + Application.temporaryCachePath, + promptWeightPath + ); + string pmtProtoPath = System.IO.Path.Combine( + Application.temporaryCachePath, + promptProtoPath + ); + // string mlpPath = System.IO.Path.Combine( + // Application.temporaryCachePath, + // mlpWeightPath + // ); + // string mlpProPath = System.IO.Path.Combine( + // Application.temporaryCachePath, + // mlpProtoPath + // ); + + encoder = new ailia.AiliaModel(); + decoder = new ailia.AiliaModel(); + // memAttention = new ailia.AiliaModel(); + // encoderMem = new ailia.AiliaModel(); + prompt = new ailia.AiliaModel(); + // mlp = new ailia.AiliaModel(); + + uint memory_mode = + ailia.Ailia.AILIA_MEMORY_REDUCE_CONSTANT + | ailia.Ailia.AILIA_MEMORY_REDUCE_CONSTANT_WITH_INPUT_INITIALIZER + | ailia.Ailia.AILIA_MEMORY_REUSE_INTERSTAGE; + memory_mode = ailia.Ailia.AILIA_MEMORY_REDUCE_INTERSTAGE; + encoder.SetMemoryMode(memory_mode); + decoder.SetMemoryMode(memory_mode); + // memAttention.SetMemoryMode(memory_mode); + // encoderMem.SetMemoryMode(memory_mode); + prompt.SetMemoryMode(memory_mode); + // mlp.SetMemoryMode(memory_mode); + + this.gpuMode = gpuMode; + if (gpuMode) + { + encoder.Environment(ailia.Ailia.AILIA_ENVIRONMENT_TYPE_GPU); + decoder.Environment(ailia.Ailia.AILIA_ENVIRONMENT_TYPE_GPU); + // memAttention.Environment(ailia.Ailia.AILIA_ENVIRONMENT_TYPE_GPU); + // encoderMem.Environment(ailia.Ailia.AILIA_ENVIRONMENT_TYPE_GPU); + prompt.Environment(ailia.Ailia.AILIA_ENVIRONMENT_TYPE_GPU); + // mlp.Environment(ailia.Ailia.AILIA_ENVIRONMENT_TYPE_GPU); + } + + bool encOpened = false; + bool decOpened = false; + // bool memOpened = false; + // bool encMemOpened = false; + bool promptOpened = false; + // bool mlpOpened = false; + + encOpened = encoder.OpenFile(encProtoPath, encPath); + decOpened = decoder.OpenFile(decProtoPath, decPath); + // memOpened = memAttention.OpenFile(memAttProtoPath, memAttPath); + // encMemOpened = encoderMem.OpenFile(encMemProtoPath, encMemPath); + promptOpened = prompt.OpenFile(pmtProtoPath, pmtPath); + // mlpOpened = mlp.OpenFile(mlpProPath, mlpPath); + + if (!encOpened || !decOpened || !promptOpened) + { + throw new Exception("Failed to open SAM 2 model files"); + } + + modelsInitialized = true; + } + catch (Exception e) + { + Debug.LogError($"Error while loading SAM model: {e.Message}\n{e.StackTrace}"); + modelsInitialized = false; + } + + return modelsInitialized; + } + + public float[,] GetClickPoints(int imageHeight) + { + float[,] points = new float[clickPoints.Count + (addBoxCoords ? 2 : 0), 2]; + int i = 0; + + foreach (var point in clickPoints) + { + points[i, 0] = point.x; + points[i, 1] = point.y; + + i += 1; + } + + if (addBoxCoords) + { + points[clickPoints.Count, 0] = boxCoords.xMin; + points[clickPoints.Count, 1] = boxCoords.yMin; + points[clickPoints.Count + 1, 0] = boxCoords.xMax; + points[clickPoints.Count + 1, 1] = boxCoords.yMax; + } + + return points; + } + + private float[] GetPointLabels() + { + float[] labels = new float[clickPoints.Count + (addBoxCoords ? 2 : 0)]; + + for (int i = 0; i < clickPoints.Count; ++i) + { + labels[i] = (clickPointLabels[i] ? 1f : 0f); + } + + if (addBoxCoords) + { + labels[clickPoints.Count] = 2; + labels[clickPoints.Count + 1] = 3; + } + + return labels; + } + + // Run Embedding + + private void RunEmbedding(Color32[] image, int imgWidth, int imgHeight) + { + if (isQuitting || !modelsInitialized || encoder == null || decoder == null) + { + return; + } + + float[,,,] inputTensor = PreprocessImage(image, imgWidth, imgHeight, targetSize); + // var (inputData, inputSize) = PreprocessImage2(image, imgWidth, imgHeight); + float[] nchw = Flatten4D(inputTensor); + // float[] nchw = inputData; + + try + { + int imgIndex = encoder.FindBlobIndexByName("input_image"); + + // Set encoder input shape (1x3x1024x1024) + ailia.Ailia.AILIAShape encInputShape = new ailia.Ailia.AILIAShape(); + encInputShape.dim = 4; + encInputShape.w = 1; // batch=1 + encInputShape.z = 3; // channels=3 (RGB) + encInputShape.y = (uint)targetSize; // height=1024 + encInputShape.x = (uint)targetSize; // width=1024 + + if (isQuitting || encoder == null) + { + return; + } + + bool shapeSetResult = encoder.SetInputBlobShape(encInputShape, imgIndex); + if (isQuitting || !shapeSetResult) + { + Debug.LogError("Failed to set encoder input shape: " + encoder.Status); + return; + } + + bool dataSetResult = encoder.SetInputBlobData(nchw, imgIndex); + // Debug.Log($"updated SET DATA {dataSetResult}"); + + // Run encoder + bool encResult = encoder.Update(); + + if (isQuitting || encoder == null || decoder == null) + { + return; + } + + if (!encResult) + { + Debug.LogError("Encoder inference failed: " + encoder.Status); + return; + } + + int visionFeaturesBlobIndex = encoder.FindBlobIndexByName("vision_features"); + int visionPosEnc0BlobIndex = encoder.FindBlobIndexByName("vision_pos_enc_0"); + int visionPosEnc1BlobIndex = encoder.FindBlobIndexByName("vision_pos_enc_1"); + int visionPosEnc2BlobIndex = encoder.FindBlobIndexByName("vision_pos_enc_2"); + int backboneFpn0BlobIndex = encoder.FindBlobIndexByName("backbone_fpn_0"); + int backboneFpn1BlobIndex = encoder.FindBlobIndexByName("backbone_fpn_1"); + int backboneFpn2BlobIndex = encoder.FindBlobIndexByName("backbone_fpn_2"); + + if ( + visionFeaturesBlobIndex < 0 + || visionPosEnc0BlobIndex < 0 + || visionPosEnc1BlobIndex < 0 + || visionPosEnc2BlobIndex < 0 + || backboneFpn0BlobIndex < 0 + || backboneFpn1BlobIndex < 0 + || backboneFpn2BlobIndex < 0 + ) + { + Debug.LogError("Could not find required blobs"); + return; + } + + if (isQuitting || encoder == null) + { + return; + } + + // Get blob shapes + ailia.Ailia.AILIAShape visionFeaturesBlobShape = encoder.GetBlobShape( + (uint)visionFeaturesBlobIndex + ); + + float[] visionFeaturesOutput = new float[ + visionFeaturesBlobShape.w + * visionFeaturesBlobShape.z + * visionFeaturesBlobShape.y + * visionFeaturesBlobShape.x + ]; + + ailia.Ailia.AILIAShape visionPosEnc0BlobShape = encoder.GetBlobShape( + (uint)visionPosEnc0BlobIndex + ); + + float[] visionPosEnc0Output = new float[ + visionPosEnc0BlobShape.w + * visionPosEnc0BlobShape.z + * visionPosEnc0BlobShape.y + * visionPosEnc0BlobShape.x + ]; + + ailia.Ailia.AILIAShape visionPosEnc1BlobShape = encoder.GetBlobShape( + (uint)visionPosEnc1BlobIndex + ); + + float[] visionPosEnc1Output = new float[ + visionPosEnc1BlobShape.w + * visionPosEnc1BlobShape.z + * visionPosEnc1BlobShape.y + * visionPosEnc1BlobShape.x + ]; + + ailia.Ailia.AILIAShape visionPosEnc2BlobShape = encoder.GetBlobShape( + (uint)visionPosEnc2BlobIndex + ); + + float[] visionPosEnc2Output = new float[ + visionPosEnc2BlobShape.w + * visionPosEnc2BlobShape.z + * visionPosEnc2BlobShape.y + * visionPosEnc2BlobShape.x + ]; + + ailia.Ailia.AILIAShape backboneFpn0BlobShape = encoder.GetBlobShape( + (uint)backboneFpn0BlobIndex + ); + + float[] backboneFpn0Output = new float[ + backboneFpn0BlobShape.w + * backboneFpn0BlobShape.z + * backboneFpn0BlobShape.y + * backboneFpn0BlobShape.x + ]; + + ailia.Ailia.AILIAShape backboneFpn1BlobShape = encoder.GetBlobShape( + (uint)backboneFpn1BlobIndex + ); + + float[] backboneFpn1Output = new float[ + backboneFpn1BlobShape.w + * backboneFpn1BlobShape.z + * backboneFpn1BlobShape.y + * backboneFpn1BlobShape.x + ]; + + ailia.Ailia.AILIAShape backboneFpn2BlobShape = encoder.GetBlobShape( + (uint)backboneFpn2BlobIndex + ); + + float[] backboneFpn2Output = new float[ + backboneFpn2BlobShape.w + * backboneFpn2BlobShape.z + * backboneFpn2BlobShape.y + * backboneFpn2BlobShape.x + ]; + + encoder.GetBlobData(visionFeaturesOutput, visionFeaturesBlobIndex); + encoder.GetBlobData(visionPosEnc0Output, visionPosEnc0BlobIndex); + encoder.GetBlobData(visionPosEnc1Output, visionPosEnc1BlobIndex); + encoder.GetBlobData(visionPosEnc2Output, visionPosEnc2BlobIndex); + encoder.GetBlobData(backboneFpn0Output, backboneFpn0BlobIndex); + encoder.GetBlobData(backboneFpn1Output, backboneFpn1BlobIndex); + encoder.GetBlobData(backboneFpn2Output, backboneFpn2BlobIndex); + + float[][,,,] visionPosEnc = new float[][,,,] + { + ReshapeTo4D( + visionPosEnc0Output, + (int)visionPosEnc0BlobShape.w, + (int)visionPosEnc0BlobShape.z, + (int)visionPosEnc0BlobShape.y, + (int)visionPosEnc0BlobShape.x + ), + ReshapeTo4D( + visionPosEnc1Output, + (int)visionPosEnc1BlobShape.w, + (int)visionPosEnc1BlobShape.z, + (int)visionPosEnc1BlobShape.y, + (int)visionPosEnc1BlobShape.x + ), + ReshapeTo4D( + visionPosEnc2Output, + (int)visionPosEnc2BlobShape.w, + (int)visionPosEnc2BlobShape.z, + (int)visionPosEnc2BlobShape.y, + (int)visionPosEnc2BlobShape.x + ), + }; + + float[][,,,] backboneFpn = new float[][,,,] + { + ReshapeTo4D( + backboneFpn0Output, + (int)backboneFpn0BlobShape.w, + (int)backboneFpn0BlobShape.z, + (int)backboneFpn0BlobShape.y, + (int)backboneFpn0BlobShape.x + ), + ReshapeTo4D( + backboneFpn1Output, + (int)backboneFpn1BlobShape.w, + (int)backboneFpn1BlobShape.z, + (int)backboneFpn1BlobShape.y, + (int)backboneFpn1BlobShape.x + ), + ReshapeTo4D( + backboneFpn2Output, + (int)backboneFpn2BlobShape.w, + (int)backboneFpn2BlobShape.z, + (int)backboneFpn2BlobShape.y, + (int)backboneFpn2BlobShape.x + ) + }; + + backboneData.visionFeatures = ReshapeTo4D( + visionFeaturesOutput, + (int)visionFeaturesBlobShape.w, + (int)visionFeaturesBlobShape.z, + (int)visionFeaturesBlobShape.y, + (int)visionFeaturesBlobShape.x + ); + backboneData.visionPosEnc = visionPosEnc; + backboneData.backboneFpn = backboneFpn; + + float[][,,] visionFeats = PrepareBackboneFeatures(backboneData); + + // no_mem_embed = self.trunc_normal((1, 1, 256), std=0.02).astype(np.float32) + int hidden_dim = 256; + float[,,] noMemEmbed = TruncNormal(1, 1, hidden_dim, 0.02f); + float[,,] lastFeat = visionFeats[visionFeats.Length - 1]; + float[,,] updatedFeat = BroadcastAdd3D(lastFeat, noMemEmbed); + visionFeats[visionFeats.Length - 1] = updatedFeat; + + (int height, int width)[] bbFeatSizes = new (int, int)[] + { + (256, 256), + (128, 128), + (64, 64) + }; + + // feats = [ + // np.transpose(feat, (1, 2, 0)).reshape(1, -1, *feat_size) + // for feat, feat_size in zip(vision_feats[::-1], bb_feat_sizes[::-1]) + // ][::-1] + float[][,,,] featsArray = new float[visionFeats.Length][,,,]; + for (int i = 0; i < visionFeats.Length; i++) + { + int revIndex = visionFeats.Length - 1 - i; + float[,,] feat = visionFeats[revIndex]; // shape: (HW, 1, C) + (int H, int W) = bbFeatSizes[revIndex]; // H, W + + int HW = feat.GetLength(0); + int one = feat.GetLength(1); // should be 1 + int C = feat.GetLength(2); + + if (HW != H * W) + throw new InvalidOperationException($"Expected HW={H * W}, but got {HW}"); + + // Transpose to (1, C, HW) + float[,,] transposed = new float[1, C, HW]; + for (int hw = 0; hw < HW; hw++) + { + for (int c = 0; c < C; c++) + { + transposed[0, c, hw] = feat[hw, 0, c]; + } + } + + // Reshape (1, C, HW) → (1, C, H, W) + float[,,,] reshaped = new float[1, C, H, W]; + for (int hw = 0; hw < HW; hw++) + { + int h = hw / W; + int w = hw % W; + for (int c = 0; c < C; c++) + { + reshaped[0, c, h, w] = transposed[0, c, hw]; + } + } + + featsArray[i] = reshaped; + } + + Array.Reverse(featsArray); + // features = {"image_embed": feats[-1], "high_res_feats": feats[:-1]} + + float[,,,] lastFeatElement = featsArray[featsArray.Length - 1]; + + float[][,,,] allButLast = featsArray.Take(featsArray.Length - 1).ToArray(); + + encoderOutput = new float[ + visionFeaturesBlobShape.w + * visionFeaturesBlobShape.z + * visionFeaturesBlobShape.y + * visionFeaturesBlobShape.x + ]; + + encoderOutput = Flatten4D(lastFeatElement); + Debug.Log("encoderOutput"); + highResFeats = new float[featsArray.Length - 1][]; + for (int i = 0; i < allButLast.Length; i++) + { + highResFeats[i] = Flatten4D(allButLast[i]); + } + } + catch (Exception e) + { + Debug.LogError("Inference error: " + e.Message + "\n" + e.StackTrace); + } + } + + private float[,,] BroadcastAdd3D(float[,,] a, float[,,] b) + { + int a0 = a.GetLength(0); + int a1 = a.GetLength(1); + int a2 = a.GetLength(2); + + int b0 = b.GetLength(0); + int b1 = b.GetLength(1); + int b2 = b.GetLength(2); + + // Check dimension compatibility (broadcasting rules) + if ((b0 != 1 && b0 != a0) || (b1 != 1 && b1 != a1) || (b2 != 1 && b2 != a2)) + throw new ArgumentException("Incompatible shapes for broadcasting."); + + float[,,] result = new float[a0, a1, a2]; + + for (int i = 0; i < a0; i++) + { + for (int j = 0; j < a1; j++) + { + for (int k = 0; k < a2; k++) + { + float valA = a[i, j, k]; + float valB = b[b0 == 1 ? 0 : i, b1 == 1 ? 0 : j, b2 == 1 ? 0 : k]; + + result[i, j, k] = valA + valB; + } + } + } + + return result; + } + + private float[,] ResizeBilinear(float[,] input, int newH, int newW) + { + int srcH = input.GetLength(0); + int srcW = input.GetLength(1); + float[,] result = new float[newH, newW]; + + float scaleY = (float)srcH / newH; + float scaleX = (float)srcW / newW; + + for (int y = 0; y < newH; y++) + { + float srcY = y * scaleY; + int y0 = (int)Math.Floor(srcY); + int y1 = Math.Min(y0 + 1, srcH - 1); + float wy = srcY - y0; + + for (int x = 0; x < newW; x++) + { + float srcX = x * scaleX; + int x0 = (int)Math.Floor(srcX); + int x1 = Math.Min(x0 + 1, srcW - 1); + float wx = srcX - x0; + + float top = (1 - wx) * input[y0, x0] + wx * input[y0, x1]; + float bottom = (1 - wx) * input[y1, x0] + wx * input[y1, x1]; + result[y, x] = (1 - wy) * top + wy * bottom; + } + } + + return result; + } + + private float[][,,] PrepareBackboneFeatures(BackboneOutputs backboneData) + { + int numFeatureLevels = 3; + + float[][,,,] featureMaps = backboneData.backboneFpn.TakeLast(numFeatureLevels).ToArray(); + // for (int i = 0; i < featureMaps.Length; i++) + // { + // Debug.Log(featureMaps[i].Length); + // } + // float[][] visionPosEmbeds = backboneData.visionPosEnc.TakeLast(numFeatureLevels).ToArray(); + + // float[][,,,] visionPosEmbeds4D = new float[3][,,,] + // { + // ReshapeTo4D(visionPosEmbeds[0], 1, 256, 256, 256), + // ReshapeTo4D(visionPosEmbeds[1], 1, 256, 128, 128), + // ReshapeTo4D(visionPosEmbeds[2], 1, 256, 64, 64) + // }; + + // float[][,,,] featureMaps4D = new float[3][,,,] + // { + // ReshapeTo4D(featureMaps[0], 1, 128, 128, 128), + // ReshapeTo4D(featureMaps[1], 1, 256, 64, 64), + // ReshapeTo4D(featureMaps[2], 1, 256, 64, 64) + // }; + + float[][,,] visionFeats = new float[numFeatureLevels][,,]; + + for (int i = 0; i < numFeatureLevels; i++) + { + float[,,,] x = featureMaps[i]; + int N = x.GetLength(0); + int C = x.GetLength(1); + int H = x.GetLength(2); + int W = x.GetLength(3); + int HW = H * W; + + float[,,] output = new float[HW, N, C]; + for (int n = 0; n < N; n++) + { + for (int c = 0; c < C; c++) + { + for (int h = 0; h < H; h++) + { + for (int w = 0; w < W; w++) + { + int hw = h * W + w; + output[hw, n, c] = x[n, c, h, w]; + } + } + } + } + + visionFeats[i] = output; + } + + // (int, int)[] feat_sizes = visionPosEmbeds4D + // .Select(x => (height: x.GetLength(2), width: x.GetLength(3))) + // .ToArray(); + + // float[][,,] processed = ProcessVisionPosEmbeds(visionPosEmbeds4D); + + return visionFeats; + } + + public float[,,] TruncNormal( + int dim0, + int dim1, + int dim2, + float std = 0.02f, + float a = -2f, + float b = 2f + ) + { + float[,,] values = new float[dim0, dim1, dim2]; + + for (int i = 0; i < dim0; i++) + for (int j = 0; j < dim1; j++) + for (int k = 0; k < dim2; k++) + { + float val; + do + { + val = NextGaussian(0f, std); + } while (val < a * std || val > b * std); + values[i, j, k] = val; + } + + return values; + } + + // Generates one sample from a Gaussian distribution using Box-Muller transform + private float NextGaussian(float mean = 0, float stdDev = 1) + { + // Use Box-Muller transform to generate a normal distributed value + double u1 = 1.0 - _rng.NextDouble(); // uniform(0,1] random doubles + double u2 = 1.0 - _rng.NextDouble(); + double randStdNormal = Math.Sqrt(-2.0 * Math.Log(u1)) * Math.Sin(2.0 * Math.PI * u2); // random normal(0,1) + return (float)(mean + stdDev * randStdNormal); + } + + private float[] Flatten4D(float[,,,] input) + { + int N = input.GetLength(0); + int C = input.GetLength(1); + int H = input.GetLength(2); + int W = input.GetLength(3); + + float[] flat = new float[N * C * H * W]; + int index = 0; + + for (int n = 0; n < N; n++) + for (int c = 0; c < C; c++) + for (int h = 0; h < H; h++) + for (int w = 0; w < W; w++) + flat[index++] = input[n, c, h, w]; + + return flat; + } + + private float[,,] ReshapeTo3D(float[] flat, int z, int y, int x) + { + if (flat.Length != z * y * x) + throw new ArgumentException( + $"Input length {flat.Length} does not match shape ({z}, {y}, {x})" + ); + + float[,,] result = new float[z, y, x]; + int index = 0; + + for (int i = 0; i < z; i++) + for (int j = 0; j < y; j++) + for (int k = 0; k < x; k++) + result[i, j, k] = flat[index++]; + + return result; + } + + private float[,,,] ReshapeTo4D(float[] array, int w, int z, int y, int x) + { + if (array.Length != w * z * y * x) + throw new ArgumentException( + "flatArray length does not match the product of dimensions" + ); + + float[,,,] array4D = new float[w, z, y, x]; + int index = 0; + for (int i = 0; i < w; i++) + { + for (int j = 0; j < z; j++) + { + for (int k = 0; k < y; k++) + { + for (int l = 0; l < x; l++) + { + array4D[i, j, k, l] = array[index++]; + } + } + } + } + return array4D; + } + + private float[,,] FourReshapeTo3D(float[,,,] input) + { + int d0 = input.GetLength(0); + int d1 = input.GetLength(1); + int d2 = input.GetLength(2); + int d3 = input.GetLength(3); + + int d23 = d2 * d3; + float[,,] output = new float[d0, d1, d23]; + + for (int i0 = 0; i0 < d0; i0++) + { + for (int i1 = 0; i1 < d1; i1++) + { + for (int i2 = 0; i2 < d2; i2++) + { + for (int i3 = 0; i3 < d3; i3++) + { + output[i0, i1, i2 * d3 + i3] = input[i0, i1, i2, i3]; + } + } + } + } + + return output; + } + + // Transpose axes (2, 0, 1) of 3D array + // input shape: [d0, d1, d2] + // output shape: [d2, d0, d1] + private float[,,] Transpose201(float[,,] input) + { + int d0 = input.GetLength(0); + int d1 = input.GetLength(1); + int d2 = input.GetLength(2); + + float[,,] output = new float[d2, d0, d1]; + + for (int i0 = 0; i0 < d0; i0++) + { + for (int i1 = 0; i1 < d1; i1++) + { + for (int i2 = 0; i2 < d2; i2++) + { + output[i2, i0, i1] = input[i0, i1, i2]; + } + } + } + + return output; + } + + // Process all vision_pos_embeds arrays similarly to the python list comprehension + private float[][,,] ProcessVisionPosEmbeds(float[][,,,] visionPosEmbeds4D) + { + int n = visionPosEmbeds4D.Length; + float[][,,] output = new float[n][,,]; + + for (int i = 0; i < n; i++) + { + float[,,,] current4D = visionPosEmbeds4D[i]; + float[,,] reshaped = FourReshapeTo3D(current4D); + float[,,] transposed = Transpose201(reshaped); + output[i] = transposed; + } + return output; + } + + private struct InputData + { + public Vector2[] inputPoints; + public int[] inputLabels; + public Vector4? inputBox; // x1, y1, x2, y2 or similar + } + + private struct BackboneOutputs + { + public float[,,,] visionFeatures; + public float[][,,,] visionPosEnc; + public float[][,,,] backboneFpn; + } + + private InputData GetInputPoint( + List posPoints, + List negPoints, + Vector4? box = null + ) + { + // Handle nulls like Python version + if (posPoints == null) + { + if (negPoints == null && box == null) + { + posPoints = new List { new Vector2(0, 0) }; // <-- replace with actual default POINT1 + } + else + { + posPoints = new List(); + } + } + + if (negPoints == null) + { + negPoints = new List(); + } + + List inputPoints = new List(); + List inputLabels = new List(); + + foreach (var pt in posPoints) + { + inputPoints.Add(pt); + inputLabels.Add(1); + } + + foreach (var pt in negPoints) + { + inputPoints.Add(pt); + inputLabels.Add(0); + } + + return new InputData + { + inputPoints = inputPoints.ToArray(), + inputLabels = inputLabels.ToArray(), + inputBox = box + }; + } + + List ConvertFloatArrayToVector2List(float[,] points) + { + int rows = points.GetLength(0); + int cols = points.GetLength(1); + + if (cols != 2) + throw new System.ArgumentException("Input must have shape [N, 2]"); + + List result = new List(); + for (int i = 0; i < rows; i++) + { + float x = points[i, 0]; + float y = points[i, 1]; + result.Add(new Vector2(x, y)); + } + + return result; + } + + public struct ConcatPoints + { + public Vector2[] coords; + public int[] labels; + } + + // Run Inference + private (bool[][,], float[]) RunInference( + int imgWidth, + int imgHeight, + float[,] pointCoords, + float[] pointLabels + ) + { + if ( + isQuitting || !modelsInitialized || encoder == null || decoder == null || prompt == null + ) + { + return (new bool[0][,], new float[0]); + } + if (pointCoords.Length == 0) + { + return (new bool[0][,], new float[0]); + } + + try + { + // Call the method + List posPoints = ConvertFloatArrayToVector2List(pointCoords); + InputData inputData = GetInputPoint(posPoints, null, null); + + // // Unpack the result + Vector2[] point_coords = inputData.inputPoints; + int[] point_labels = inputData.inputLabels; + Vector4? input_box = inputData.inputBox; + + ConcatPoints? concatPoints = null; + + if (point_coords != null && point_coords.Length > 0) + { + concatPoints = new ConcatPoints { coords = point_coords, labels = point_labels }; + } + + if (input_box.HasValue) + { + // Convert Vector4 box → 2 corner points + Vector4 box = input_box.Value; + Vector2 topLeft = new Vector2(box.x, box.y); + Vector2 bottomRight = new Vector2(box.z, box.w); + + Vector2[] boxCoords = new Vector2[] { topLeft, bottomRight }; + int[] boxLabels = new int[] { 2, 3 }; + + if (point_coords != null && point_coords.Length > 0) + { + // Merge box points + labels with user points + Vector2[] concatCoords = new Vector2[boxCoords.Length + point_coords.Length]; + int[] concatLabels = new int[boxLabels.Length + point_labels.Length]; + + boxCoords.CopyTo(concatCoords, 0); + point_coords.CopyTo(concatCoords, boxCoords.Length); + + boxLabels.CopyTo(concatLabels, 0); + point_labels.CopyTo(concatLabels, boxLabels.Length); + + concatPoints = new ConcatPoints + { + coords = concatCoords, + labels = concatLabels + }; + } + else + { + // Only box points + concatPoints = new ConcatPoints { coords = boxCoords, labels = boxLabels }; + } + } + else if (point_coords != null && point_coords.Length > 0) + { + // Only point prompts + concatPoints = new ConcatPoints { coords = point_coords, labels = point_labels }; + } + + if (concatPoints == null) + { + throw new System.Exception("concatPoints must exist"); + } + + float[,] scaledCoords = ApplyCoordinateScaling(pointCoords, imgHeight, imgWidth); + + // Prepare point coordinates and labels + int pointCount = pointLabels.Length; + float[] flattenedCoords = new float[pointCount * 2]; + for (int i = 0; i < pointCount; i++) + { + flattenedCoords[i * 2] = scaledCoords[i, 0]; + flattenedCoords[i * 2 + 1] = scaledCoords[i, 1]; + } + + // float[,,] maskInputDummy; + float[] maskInputDummy; + float[] masksEnable; + + // if (maskInput == null) + // { + maskInputDummy = new float[1 * 256 * 256]; + // maskInputDummy = new float[1, 256, 256]; + masksEnable = new float[1] { 0f }; + // } + // else + // { + // maskInputDummy = maskInput; + // masksEnable = new int[] { 1 }; + // } + + // Get blob indices + int promptCoordsIndex = prompt.FindBlobIndexByName("coords"); + int promptLabelsIndex = prompt.FindBlobIndexByName("labels"); + int promptMasksIndex = prompt.FindBlobIndexByName("masks"); + int promptMasksEnabledIndex = prompt.FindBlobIndexByName("masks_enable"); + if ( + promptCoordsIndex < 0 + || promptLabelsIndex < 0 + || promptMasksIndex < 0 + || promptMasksEnabledIndex < 0 + ) + { + Debug.LogError("Failed to find required common blob indices"); + return (new bool[0][,], new float[0]); + } + + // point_coords: 1x1x2 + ailia.Ailia.AILIAShape concatPointShape = new ailia.Ailia.AILIAShape(); + concatPointShape.dim = 3; + concatPointShape.z = 1; // batch=1 + concatPointShape.y = 1; // points count (1) + concatPointShape.x = 2; // 2D coords (x,y) + + // // point_labels: 1x1 + ailia.Ailia.AILIAShape labelsShape = new ailia.Ailia.AILIAShape(); + labelsShape.dim = 2; + labelsShape.y = 1; // batch=1 + labelsShape.x = 1; // points count (1) + + // maskunput dummy + ailia.Ailia.AILIAShape masksShape = new ailia.Ailia.AILIAShape(); + masksShape.dim = 3; + masksShape.z = 1; + masksShape.y = 256; + masksShape.x = 256; + + ailia.Ailia.AILIAShape masksEnableShape = new ailia.Ailia.AILIAShape(); + masksEnableShape.dim = 1; + masksEnableShape.x = 1; + + bool concatPointShapeResult = prompt.SetInputBlobShape( + concatPointShape, + (uint)promptCoordsIndex + ); + bool labelsShapeResult = prompt.SetInputBlobShape(labelsShape, (uint)promptLabelsIndex); + + bool masksShapeResult = prompt.SetInputBlobShape(masksShape, (uint)promptMasksIndex); + + bool masksEnabledShapeResult = prompt.SetInputBlobShape( + masksEnableShape, + (uint)promptMasksEnabledIndex + ); + + for (int i = 0; i < flattenedCoords.Length; i++) + { + Debug.Log(flattenedCoords[i]); + } + bool setCoordsResult = prompt.SetInputBlobData( + flattenedCoords, + (uint)promptCoordsIndex + ); + + bool setlabelsResult = prompt.SetInputBlobData(pointLabels, (uint)promptLabelsIndex); + + bool setMaskseResult = prompt.SetInputBlobData(maskInputDummy, (uint)promptMasksIndex); + + bool setMasksEnabledResult = prompt.SetInputBlobData( + masksEnable, + (uint)promptMasksEnabledIndex + ); + + if (!setCoordsResult || !setlabelsResult || !masksEnabledShapeResult) + { + Debug.LogError("Failed to set required common blob indices"); + return (new bool[0][,], new float[0]); + } + + // Run prompt + bool promptResult = prompt.Update(); + + if (isQuitting || prompt == null) + { + return (new bool[0][,], new float[0]); + } + + if (!promptResult) + { + Debug.LogError( + "Prompt inference failed: " + + prompt.Status + + " [" + + prompt.GetErrorDetail() + + "]" + ); + return (new bool[0][,], new float[0]); + } + + if (isQuitting || prompt == null) + { + return (new bool[0][,], new float[0]); + } + + int sparseEmbeddingsBlobIndex = prompt.FindBlobIndexByName("sparse_embeddings"); + int denseEmbeddingsBlobIndex = prompt.FindBlobIndexByName("dense_embeddings"); + int densePeBlobIndex = prompt.FindBlobIndexByName("dense_pe"); + + if ( + sparseEmbeddingsBlobIndex < 0 + || denseEmbeddingsBlobIndex < 0 + || densePeBlobIndex < 0 + ) + { + Debug.LogError( + "Could not find sparse_embeddings, dense_embeddings and dense_pe blobs" + ); + return (new bool[0][,], new float[0]); + } + + if (isQuitting || prompt == null) + { + return (new bool[0][,], new float[0]); + } + + // Get blob shapes + ailia.Ailia.AILIAShape sparseEmbeddingsBlobShape = prompt.GetBlobShape( + (uint)sparseEmbeddingsBlobIndex + ); + + float[] sparseEmbeddingsOutput = new float[ + sparseEmbeddingsBlobShape.z + * sparseEmbeddingsBlobShape.y + * sparseEmbeddingsBlobShape.x + ]; + + ailia.Ailia.AILIAShape denseEmbeddingsBlobShape = prompt.GetBlobShape( + (uint)denseEmbeddingsBlobIndex + ); + + float[] denseEmbeddingsOutput = new float[ + denseEmbeddingsBlobShape.w + * denseEmbeddingsBlobShape.z + * denseEmbeddingsBlobShape.y + * denseEmbeddingsBlobShape.x + ]; + + ailia.Ailia.AILIAShape densePeBlobShape = prompt.GetBlobShape((uint)densePeBlobIndex); + + float[] densePeOutput = new float[ + densePeBlobShape.w * densePeBlobShape.z * densePeBlobShape.y * densePeBlobShape.x + ]; + + prompt.GetBlobData(sparseEmbeddingsOutput, sparseEmbeddingsBlobIndex); + prompt.GetBlobData(denseEmbeddingsOutput, denseEmbeddingsBlobIndex); + prompt.GetBlobData(densePeOutput, densePeBlobIndex); + + // Identify mask and score blobs + int imageEmbeddingsIndex = decoder.FindBlobIndexByName("image_embeddings"); + int imagePeIndex = decoder.FindBlobIndexByName("image_pe"); + int sparsePromptEmbeddingsIndex = decoder.FindBlobIndexByName( + "sparse_prompt_embeddings" + ); + int densePromptEmbeddingsIndex = decoder.FindBlobIndexByName("dense_prompt_embeddings"); + int highResFeatures1Index = decoder.FindBlobIndexByName("high_res_features1"); + int highResFeatures2Index = decoder.FindBlobIndexByName("high_res_features2"); + + ailia.Ailia.AILIAShape imageEmbeddingsShape = new ailia.Ailia.AILIAShape(); + imageEmbeddingsShape.dim = 4; + imageEmbeddingsShape.w = 1; // batch=1 + imageEmbeddingsShape.z = 256; // channel=256 + imageEmbeddingsShape.y = 64; // height=64 + imageEmbeddingsShape.x = 64; // width=64 + + ailia.Ailia.AILIAShape imagePeShape = new ailia.Ailia.AILIAShape(); + imagePeShape.dim = 4; + imagePeShape.w = densePeBlobShape.w; // batch=1 + imagePeShape.z = densePeBlobShape.z; // channel=256 + imagePeShape.y = densePeBlobShape.y; // height=64 + imagePeShape.x = densePeBlobShape.x; // width=64 + + ailia.Ailia.AILIAShape sparsePromptEmbeddingsShape = new ailia.Ailia.AILIAShape(); + sparsePromptEmbeddingsShape.dim = 3; + sparsePromptEmbeddingsShape.z = sparseEmbeddingsBlobShape.z; + sparsePromptEmbeddingsShape.y = sparseEmbeddingsBlobShape.y; + sparsePromptEmbeddingsShape.x = sparseEmbeddingsBlobShape.x; + + ailia.Ailia.AILIAShape densePromptEmbeddingsShape = new ailia.Ailia.AILIAShape(); + densePromptEmbeddingsShape.dim = 4; + densePromptEmbeddingsShape.w = denseEmbeddingsBlobShape.w; + densePromptEmbeddingsShape.z = denseEmbeddingsBlobShape.z; + densePromptEmbeddingsShape.y = denseEmbeddingsBlobShape.y; + densePromptEmbeddingsShape.x = denseEmbeddingsBlobShape.x; + + ailia.Ailia.AILIAShape highResFeatures1Shape = new ailia.Ailia.AILIAShape(); + highResFeatures1Shape.dim = 4; + highResFeatures1Shape.w = 1; // batch=1 + highResFeatures1Shape.z = 32; // channel=256 + highResFeatures1Shape.y = 256; // height=64 + highResFeatures1Shape.x = 256; // width=64 + + ailia.Ailia.AILIAShape highResFeatures2Shape = new ailia.Ailia.AILIAShape(); + highResFeatures2Shape.dim = 4; + highResFeatures2Shape.w = 1; // batch=1 + highResFeatures2Shape.z = 64; // channel=256 + highResFeatures2Shape.y = 128; // height=64 + highResFeatures2Shape.x = 128; // width=64 + + if (imageEmbeddingsIndex < 0 || imagePeIndex < 0) + { + Debug.LogError("Could not find mask and score blobs"); + return (new bool[0][,], new float[0]); + } + + if (isQuitting || decoder == null) + { + return (new bool[0][,], new float[0]); + } + + bool imageEmbeddingsShapeResult = decoder.SetInputBlobShape( + imageEmbeddingsShape, + (uint)imageEmbeddingsIndex + ); + + bool imagePeShapeResult = decoder.SetInputBlobShape(imagePeShape, (uint)imagePeIndex); + + bool sparsePromptEmbeddingsShapeResult = decoder.SetInputBlobShape( + sparsePromptEmbeddingsShape, + (uint)sparsePromptEmbeddingsIndex + ); + + bool densePromptEmbeddingsShapeResult = decoder.SetInputBlobShape( + densePromptEmbeddingsShape, + (uint)densePromptEmbeddingsIndex + ); + + bool highResFeatures1ShapeResult = decoder.SetInputBlobShape( + highResFeatures1Shape, + (uint)highResFeatures1Index + ); + + bool highResFeatures2ShapeResult = decoder.SetInputBlobShape( + highResFeatures2Shape, + (uint)highResFeatures2Index + ); + + bool imageEmbeddingsResult = decoder.SetInputBlobData( + encoderOutput, + (uint)imageEmbeddingsIndex + ); + + bool imagePeResult = decoder.SetInputBlobData(densePeOutput, (uint)imagePeIndex); + + bool sparseEmbeddingsResult = decoder.SetInputBlobData( + sparseEmbeddingsOutput, + (uint)sparsePromptEmbeddingsIndex + ); + + bool denseEmbeddingsResult = decoder.SetInputBlobData( + denseEmbeddingsOutput, + (uint)densePromptEmbeddingsIndex + ); + + bool highResFeatures1Result = decoder.SetInputBlobData( + highResFeats[0], + (uint)highResFeatures1Index + ); + + bool highResFeatures2Result = decoder.SetInputBlobData( + highResFeats[1], + (uint)highResFeatures2Index + ); + + // Run decoder + bool decoderResult = decoder.Update(); + + if (isQuitting || decoder == null) + { + return (new bool[0][,], new float[0]); + } + + if (!decoderResult) + { + Debug.LogError( + "Prompt inference failed: " + + decoder.Status + + " [" + + decoder.GetErrorDetail() + + "]" + ); + return (new bool[0][,], new float[0]); + } + + // masks, iou_pred, sam_tokens_out, object_score_logits = mask_decoder.run + // Get blob shapes + int masksBlobIndex = decoder.FindBlobIndexByName("masks"); + int iouPredBlobIndex = decoder.FindBlobIndexByName("iou_pred"); + int samTokensOutBlobIndex = decoder.FindBlobIndexByName("sam_tokens_out"); + int objectScoreLogitsBlobIndex = decoder.FindBlobIndexByName("object_score_logits"); + ailia.Ailia.AILIAShape masksBlobShape = decoder.GetBlobShape((uint)masksBlobIndex); + float[] masksBlobOutput = new float[ + masksBlobShape.w * masksBlobShape.z * masksBlobShape.y * masksBlobShape.x + ]; + + ailia.Ailia.AILIAShape iouPredBlobShape = decoder.GetBlobShape((uint)iouPredBlobIndex); + float[] iouPredBlobOutput = new float[iouPredBlobShape.y * iouPredBlobShape.x]; + + ailia.Ailia.AILIAShape samTokensOutBlobShape = decoder.GetBlobShape( + (uint)samTokensOutBlobIndex + ); + float[] samTokensOutBlobOutput = new float[ + samTokensOutBlobShape.z * samTokensOutBlobShape.y * samTokensOutBlobShape.x + ]; + + ailia.Ailia.AILIAShape objectScoreLogitsBlobShape = decoder.GetBlobShape( + (uint)objectScoreLogitsBlobIndex + ); + float[] objectScoreLogitsBlobOutput = new float[ + objectScoreLogitsBlobShape.y * objectScoreLogitsBlobShape.x + ]; + + bool getMasksBlobResult = decoder.GetBlobData(masksBlobOutput, (uint)masksBlobIndex); + bool getiouPredBlobResult = decoder.GetBlobData( + iouPredBlobOutput, + (uint)iouPredBlobIndex + ); + bool getsamTokensBlobResult = decoder.GetBlobData( + samTokensOutBlobOutput, + (uint)samTokensOutBlobIndex + ); + + bool objectScoreLogitsBlobResult = decoder.GetBlobData( + objectScoreLogitsBlobOutput, + (uint)objectScoreLogitsBlobIndex + ); + + float[,,,] masks = ReshapeTo4D( + masksBlobOutput, + (int)masksBlobShape.w, + (int)masksBlobShape.z, + (int)masksBlobShape.y, + (int)masksBlobShape.x + ); + + float[,] iouPred = ReshapeTo2D( + iouPredBlobOutput, + (int)iouPredBlobShape.y, + (int)iouPredBlobShape.x + ); + float[,,] samTokens = ReshapeTo3D( + samTokensOutBlobOutput, + (int)samTokensOutBlobShape.z, + (int)samTokensOutBlobShape.y, + (int)samTokensOutBlobShape.x + ); + float[,] objectScore = ReshapeTo2D( + objectScoreLogitsBlobOutput, + (int)objectScoreLogitsBlobShape.y, + (int)objectScoreLogitsBlobShape.x + ); + // masks = masks[:, 1:, :, :] 1 + // float[,,,] lowResMasks = SliceChannelDim(masks); + // iou_pred = iou_pred[:, 1:] 2 + // iouPred = Slice2DColumns(iouPred, 1); + // sam_tokens_out = mask_tokens_out[:, 1:] + // samTokens = Slice3D_Dim1_From1(samTokens, 1); + // masks = self.postprocess_masks( + // low_res_masks, orig_hw + // ) + // float[,,,] resized = PostprocessMasks(lowResMasks, new int[] { imgHeight, imgWidth }); + // low_res_masks 3 + // Clip(ref lowResMasks, -32.0f, -32.0f); + // float maskThreshold = 0.0f; + // 1 + // bool[,,,] binaryMask = ThresholdMask(resized, maskThreshold); + + // sorted_ind = np.argsort(scores)[::-1] + // int[] sortedInd = ArgsortDescending(iouPred); + + // bool[,,,] newMasks = ReorderMasks(binaryMask, sortedInd); + + // bool[][,] masksResult = new bool[1][,]; + // masksResult[0] = PostprocessMask(resized, imgHeight, imgWidth); + // Debug.Log(iouPred[0, 0]); + + if (isQuitting || decoder == null) + { + return (new bool[0][,], new float[0]); + } + + int numMasks = (int)iouPredBlobShape.x; + // Debug.Log(numMasks); + int maskWidth = (int)masksBlobShape.x; + int maskHeight = (int)masksBlobShape.y; + int maskArea = maskWidth * maskHeight; + bool[][,] masksResult = new bool[numMasks][,]; + + // Debug.Log(maskWidth); + // Debug.Log(maskHeight); + // Debug.Log(maskArea); + // Debug.Log(masksBlobOutput.Length); + // float[] maskUpscaled = ResizeMask1D(masksBlobOutput, maskHeight, maskWidth, imgHeight, imgWidth); + + for (int i = 0; i < numMasks; i++) + { + float[,,,] maskTensor = ReshapeToTensor( + masksBlobOutput, + i, + maskHeight, + maskWidth, + maskArea + ); + masksResult[i] = PostprocessMask(maskTensor, imgHeight, imgWidth); + } + + return (masksResult, iouPredBlobOutput); + } + catch (Exception e) + { + Debug.LogError("Inference error: " + e.Message + "\n" + e.StackTrace); + return (new bool[0][,], new float[0]); + } + } + + // private bool[,,,] ReorderMasks(bool[,,,] masks, int[] sortedInd) + // { + // int n = sortedInd.Length; + // int c = masks.GetLength(1); + // int h = masks.GetLength(2); + // int w = masks.GetLength(3); + + // bool[,,,] reordered = new bool[n, c, h, w]; + + // for (int i = 0; i < n; i++) + // { + // int srcIndex = sortedInd[i]; + // for (int j = 0; j < c; j++) + // for (int y = 0; y < h; y++) + // for (int x = 0; x < w; x++) + // reordered[i, j, y, x] = masks[srcIndex, j, y, x]; + // } + + // return reordered; + // } + + // private int[] ArgsortDescending(float[,] scores) + // { + // int rows = scores.GetLength(0); + // int cols = scores.GetLength(1); + // int total = rows * cols; + + // // Create index-value pairs + // var indexed = new List<(int index, float value)>(total); + // for (int i = 0; i < rows; i++) + // for (int j = 0; j < cols; j++) + // indexed.Add((i * cols + j, scores[i, j])); + + // // Sort descending by value + // var sorted = indexed.OrderByDescending(x => x.value).Select(x => x.index).ToArray(); + + // return sorted; + // } + + // private float[] ResizeMask1D(float[] input, int inH, int inW, int outH, int outW) + // { + // float[] output = new float[outH * outW]; + // float yScale = (float)inH / outH; + // float xScale = (float)inW / outW; + + // for (int y = 0; y < outH; y++) + // { + // float inY = y * yScale; + // int y0 = (int)Math.Floor(inY); + // int y1 = Math.Min(y0 + 1, inH - 1); + // float yLerp = inY - y0; + + // for (int x = 0; x < outW; x++) + // { + // float inX = x * xScale; + // int x0 = (int)Math.Floor(inX); + // int x1 = Math.Min(x0 + 1, inW - 1); + // float xLerp = inX - x0; + + // // Get pixel values + // float v00 = input[y0 * inW + x0]; + // float v01 = input[y0 * inW + x1]; + // float v10 = input[y1 * inW + x0]; + // float v11 = input[y1 * inW + x1]; + + // float top = (1 - xLerp) * v00 + xLerp * v01; + // float bottom = (1 - xLerp) * v10 + xLerp * v11; + // float value = (1 - yLerp) * top + yLerp * bottom; + + // output[y * outW + x] = value; + // } + // } + + // return output; + // } + + // private void Clip(ref float[,,,] array, float minValue, float maxValue) + // { + // int d0 = array.GetLength(0); + // int d1 = array.GetLength(1); + // int d2 = array.GetLength(2); + // int d3 = array.GetLength(3); + + // for (int i0 = 0; i0 < d0; i0++) + // for (int i1 = 0; i1 < d1; i1++) + // for (int i2 = 0; i2 < d2; i2++) + // for (int i3 = 0; i3 < d3; i3++) + // { + // if (array[i0, i1, i2, i3] < minValue) + // array[i0, i1, i2, i3] = minValue; + // else if (array[i0, i1, i2, i3] > maxValue) + // array[i0, i1, i2, i3] = maxValue; + // } + // } + + // private bool[,,,] ThresholdMask(float[,,,] input, float threshold) + // { + // int d0 = input.GetLength(0); + // int d1 = input.GetLength(1); + // int d2 = input.GetLength(2); + // int d3 = input.GetLength(3); + + // bool[,,,] mask = new bool[d0, d1, d2, d3]; + + // for (int i0 = 0; i0 < d0; i0++) + // for (int i1 = 0; i1 < d1; i1++) + // for (int i2 = 0; i2 < d2; i2++) + // for (int i3 = 0; i3 < d3; i3++) + // mask[i0, i1, i2, i3] = input[i0, i1, i2, i3] > threshold; + + // return mask; + // } + + // private float[,,,] PostprocessMasks(float[,,,] masks, int[] origHW) + // { + // int N = masks.GetLength(0); + // int C = masks.GetLength(1); + // int H = masks.GetLength(2); + // int W = masks.GetLength(3); + + // int newH = origHW[0]; + // int newW = origHW[1]; + // float[,,,] output = new float[N, C, newH, newW]; + + // for (int n = 0; n < N; n++) + // { + // for (int c = 0; c < C; c++) + // { + // // Extract [H, W] slice for mask[n, c] + // float[,] src = new float[H, W]; + // for (int h = 0; h < H; h++) + // for (int w = 0; w < W; w++) + // src[h, w] = masks[n, c, h, w]; + + // // Resize using bilinear interpolation + // float[,] resized = ResizeBilinear(src, newH, newW); + + // // Store into output[n, c] + // for (int h = 0; h < newH; h++) + // for (int w = 0; w < newW; w++) + // output[n, c, h, w] = resized[h, w]; + // } + // } + + // return output; + // } + + // private float[,,,] SliceChannelDim(float[,,,] input) + // { + // int N = input.GetLength(0); + // int C = input.GetLength(1); + // int H = input.GetLength(2); + // int W = input.GetLength(3); + + // float[,,,] result = new float[N, C - 1, H, W]; + + // for (int n = 0; n < N; n++) + // for (int c = 1; c < C; c++) // start at 1 + // for (int h = 0; h < H; h++) + // for (int w = 0; w < W; w++) + // result[n, c - 1, h, w] = input[n, c, h, w]; + + // return result; + // } + + // private float[,,] Slice3D_Dim1_From1(float[,,] input, int start) + // { + // int D0 = input.GetLength(0); // A + // int D1 = input.GetLength(1); // B + // int D2 = input.GetLength(2); // C + + // if (start >= D1) + // throw new ArgumentException("Start index is out of bounds for axis 1"); + + // float[,,] output = new float[D0, D1 - start, D2]; + + // for (int i = 0; i < D0; i++) + // for (int j = 1; j < D1; j++) + // for (int k = 0; k < D2; k++) + // output[i, j - start, k] = input[i, j, k]; + + // return output; + // } + + private float[,] ReshapeTo2D(float[] flat, int rows, int cols) + { + if (flat.Length != rows * cols) + throw new ArgumentException("Size mismatch between flat array and target shape."); + + float[,] result = new float[rows, cols]; + + for (int r = 0; r < rows; r++) + for (int c = 0; c < cols; c++) + result[r, c] = flat[r * cols + c]; + + return result; + } + + // private float[,] Slice2DColumns(float[,] input, int startCol) + // { + // int rows = input.GetLength(0); + // int cols = input.GetLength(1); + + // if (startCol >= cols) + // throw new ArgumentException("startCol is out of range."); + + // int newCols = cols - startCol; + // float[,] result = new float[rows, newCols]; + + // for (int r = 0; r < rows; r++) + // for (int c = 0; c < newCols; c++) + // result[r, c] = input[r, c + startCol]; + + // return result; + // } + + // Helper to convert 1D array to 4D array + private float[,,,] ReshapeToTensor(float[] data, int maskIndex, int height, int width, int area) + { + float[,,,] tensor = new float[1, 1, height, width]; + + int offset = maskIndex * area; + for (int h = 0; h < height; h++) + { + int rowOffset = h * width; + for (int w = 0; w < width; w++) + { + tensor[0, 0, h, w] = data[offset + rowOffset + w]; + } + } + + return tensor; + } + + // Scale coordinates to target size + private float[,] ApplyCoordinateScaling(float[,] coords, int imgHeight, int imgWidth) + { + float scale = GetScale(imgWidth, imgHeight); + float[,] scaledCoords = new float[coords.GetLength(0), coords.GetLength(1)]; + + for (int i = 0; i < coords.GetLength(0); i++) + { + scaledCoords[i, 0] = coords[i, 0] * scale; + scaledCoords[i, 1] = coords[i, 1] * scale; + } + + return scaledCoords; + } + + // Overlay mask on original image + private Texture2D CreateMaskedImage( + bool[,] mask, + Color32[] pixels, + int imageWidth, + int imageHeight + ) + { + Texture2D result = new Texture2D(imageWidth, imageHeight, TextureFormat.ARGB32, false); + + int maskHeight = mask.GetLength(0); + int maskWidth = mask.GetLength(1); + + // Apply mask to original image - optimized inner loop + for (int y = 0; y < maskHeight; y++) + { + int unityY = y; + int rowOffset = unityY * imageWidth; + + for (int x = 0; x < maskWidth; x++) + { + int pixelIndex = rowOffset + x; + + if (pixelIndex >= 0 && pixelIndex < pixels.Length && mask[y, x]) + { + Color32 originalColor = pixels[pixelIndex]; + pixels[pixelIndex] = new Color32( + (byte)Mathf.Lerp(originalColor.r, MaskColor.r, 0.4f), + (byte)Mathf.Lerp(originalColor.g, MaskColor.g, 0.4f), + (byte)Mathf.Lerp(originalColor.b, MaskColor.b, 0.4f), + MaskColor.a + ); + } + } + } + + result.SetPixels32(pixels); + result.Apply(); + return result; + } + + private Texture2D CreateEmptyMaskedImage(Color32[] pixels, int imageWidth, int imageHeight) + { + Texture2D result = new Texture2D(imageWidth, imageHeight, TextureFormat.ARGB32, false); + + // Apply mask to original image - optimized inner loop + for (int y = 0; y < imageHeight; y++) + { + int unityY = y; + int rowOffset = unityY * imageWidth; + + for (int x = 0; x < imageWidth; x++) + { + int pixelIndex = rowOffset + x; + + if (pixelIndex >= 0 && pixelIndex < pixels.Length) + { + Color32 originalColor = pixels[pixelIndex]; + pixels[pixelIndex] = originalColor; + } + } + } + + result.SetPixels32(pixels); + result.Apply(); + return result; + } + + // Visualize clicked points + private Texture2D DrawClickPoints(float[,] coords, float[] labels, Texture2D image) + { + Texture2D result = new Texture2D(image.width, image.height, image.format, false); + Graphics.CopyTexture(image, result); + Color32[] pixels = result.GetPixels32(); + + int numPoints = coords.GetLength(0); + int markerSize = 15; + + for (int i = 0; i < numPoints; i++) + { + if (labels[i] >= 2) + { + continue; + } + + int px = Mathf.Clamp((int)coords[i, 0], 0, image.width - 1); + int origY = (int)coords[i, 1]; + + // Convert to Unity coordinates + int py = origY; + py = Mathf.Clamp(py, 0, image.height - 1); + + Color32 markerColor = + labels[i] == 1 ? new Color32(0, 255, 0, 255) : new Color32(0, 0, 255, 255); + + //Debug.Log($"{coords[i, 0]},{coords[i, 1]} => {px}, {py}"); + + // Draw marker with bounds checking in the loop + for (int dy = -markerSize; dy <= markerSize; dy++) + { + for (int dx = -markerSize; dx <= markerSize; dx++) + { + if (Math.Abs(dx) == Math.Abs(dy)) + { + int nx = px + dx; + int ny = py + dy; + + if (nx >= 0 && nx < image.width && ny >= 0 && ny < image.height) + { + int idx = ny * image.width + nx; + pixels[idx] = markerColor; + } + } + } + } + } + + result.SetPixels32(pixels); + result.Apply(); + return result; + } + + private float GetScale(int texWidth, int texHeight) + { + return targetSize / (float)Mathf.Max(texWidth, texHeight); + } + + // Preprocess image for model input + private (float[], ValueTuple) PreprocessImage2( + Color32[] camera, + int texWidth, + int texHeight + ) + { + // Create CHW layout data array (channel, height, width) + float[] normalizedData = new float[3 * targetSize * targetSize]; + + // Optimize by computing constants outside the inner loop + int ch0Offset = 0; + int ch1Offset = targetSize * targetSize; + int ch2Offset = 2 * targetSize * targetSize; + + float scale = GetScale(texWidth, texHeight); + + // Fill with normalized values and padding + for (int y = 0; y < targetSize; y++) + { + for (int x = 0; x < targetSize; x++) + { + float fx = x / scale; + float fy = y / scale; + Color32 v = Bilinear(camera, texWidth, texHeight, fx, fy); + + int baseIdx = y * targetSize + x; // Top2Bottom + + normalizedData[ch0Offset + baseIdx] = (v.r / 255.0f - Mean[0]) / Std[0]; + normalizedData[ch1Offset + baseIdx] = (v.g / 255.0f - Mean[1]) / Std[1]; + normalizedData[ch2Offset + baseIdx] = (v.b / 255.0f - Mean[2]) / Std[2]; + } + } + + return (normalizedData, (texHeight, texWidth)); + } + + private Color32 Bilinear(Color32[] face, int w, int h, float fx, float fy) + { + // Debug.Log("Bilinear"); + int x2 = (int)fx; + int y2 = (int)fy; + float xa = 1.0f - (fx - x2); + float xb = 1.0f - xa; + float ya = 1.0f - (fy - y2); + float yb = 1.0f - ya; + if (x2 >= w || y2 >= h || x2 < 0 || y2 < 0){ + return new Color32(0, 0, 0, 255); + } + Color32 c1 = face[y2 * w + x2]; + Color32 c2 = (x2+1 < w) ? face[y2 * w + x2 + 1] : c1; + Color32 c3 = (y2+1 < h) ? face[(y2 + 1) * w + x2] : c1; + Color32 c4 = (x2+1 < w && y2+1 < h) ? face[(y2 + 1) * w + x2 + 1] : c1; + byte r = (byte)(c1.r * xa * ya + c2.r * xb * ya + c3.r * xa * yb + c4.r * xb * yb); + byte g = (byte)(c1.g * xa * ya + c2.g * xb * ya + c3.g * xa * yb + c4.g * xb * yb); + byte b = (byte)(c1.b * xa * ya + c2.b * xb * ya + c3.b * xa * yb + c4.b * xb * yb); + return new Color32(r, g, b, 255); + } + + private float[,,,] PreprocessImage( + Color32[] inputImage, + int originalWidth, + int originalHeight, + int imageSize + ) + { + // 2. Resize image to (imageSize, imageSize) + float scale = GetScale(originalWidth, originalHeight); + int newWidth = imageSize; + int newHeight = imageSize; + Color32[] resizedImage = ResizeColor32( + inputImage, + originalWidth, + originalHeight, + newWidth, + newHeight + ); + + // 3. Convert Color32[] to float[height, width, channels] normalized 0-1 + float[,,] floatImage = Color32ArrayToFloatArray(resizedImage, newHeight, newWidth); + + // 4. Normalize per channel (subtract mean, divide std) + float[] mean = new float[] { 0.485f, 0.456f, 0.406f }; + float[] std = new float[] { 0.229f, 0.224f, 0.225f }; + + for (int h = 0; h < newHeight; h++) + { + for (int w = 0; w < newWidth; w++) + { + for (int c = 0; c < 3; c++) + { + floatImage[h, w, c] = (floatImage[h, w, c] - mean[c]) / std[c]; + } + } + } + + // 5. Transpose (H, W, C) => (C, H, W) + float[,,] chw = TransposeHWCtoCHW(floatImage); + + // 6. Add batch dimension => (1, C, H, W) + float[,,,] batch = new float[1, 3, newHeight, newWidth]; + for (int c = 0; c < 3; c++) + for (int h = 0; h < newHeight; h++) + for (int w = 0; w < newWidth; w++) + batch[0, c, h, w] = chw[c, h, w]; + + return batch; + } + + // Helper: Resize Color32[] with nearest neighbor (or implement your own) + private Color32[] ResizeColor32( + Color32[] src, + int srcWidth, + int srcHeight, + int dstWidth, + int dstHeight + ) + { + Color32[] dst = new Color32[dstWidth * dstHeight]; + for (int y = 0; y < dstHeight; y++) + { + int srcY = y * srcHeight / dstHeight; + for (int x = 0; x < dstWidth; x++) + { + int srcX = x * srcWidth / dstWidth; + dst[y * dstWidth + x] = src[srcY * srcWidth + srcX]; + } + } + return dst; + } + + // Helper: Convert Color32[] to float[height,width,channels], normalized to [0..1] + private float[,,] Color32ArrayToFloatArray(Color32[] image, int height, int width) + { + float[,,] result = new float[height, width, 3]; + for (int i = 0; i < height * width; i++) + { + Color32 c = image[i]; + int h = i / width; + int w = i % width; + result[h, w, 0] = c.r / 255f; + result[h, w, 1] = c.g / 255f; + result[h, w, 2] = c.b / 255f; + } + return result; + } + + // Helper: Transpose (H,W,C) => (C,H,W) + private float[,,] TransposeHWCtoCHW(float[,,] input) + { + int H = input.GetLength(0); + int W = input.GetLength(1); + int C = input.GetLength(2); + float[,,] output = new float[C, H, W]; + for (int h = 0; h < H; h++) + for (int w = 0; w < W; w++) + for (int c = 0; c < C; c++) + output[c, h, w] = input[h, w, c]; + return output; + } + + private bool[,] PostprocessMask(float[,,,] mask, int origHeight, int origWidth) + { + int maskHeight = mask.GetLength(2); + int maskWidth = mask.GetLength(3); + + // Final resize to targetSize + bool[,] finalMask = new bool[origHeight, origWidth]; + + for (int y = 0; y < origHeight; y++) + { + float srcY = y * maskHeight / origHeight; + int y0 = (int)Math.Floor(srcY); + int y1 = Math.Min(y0 + 1, maskHeight - 1); + float wy = srcY - y0; + + for (int x = 0; x < origWidth; x++) + { + float srcX = x * maskWidth / origWidth; + int x0 = (int)Math.Floor(srcX); + int x1 = Math.Min(x0 + 1, maskWidth - 1); + float wx = srcX - x0; + + // Bilinear interpolation + float val = + (1 - wy) * (1 - wx) * mask[0, 0, y0, x0] + + wy * (1 - wx) * mask[0, 0, y1, x0] + + (1 - wy) * wx * mask[0, 0, y0, x1] + + wy * wx * mask[0, 0, y1, x1]; + + finalMask[y, x] = val > 0; + } + } + + return finalMask; + } + + // Calculate embedding of input image + // image : top bottom format + public void ProcessEmbedding(Color32[] image, int imageWidth, int imageHeight) + { + if (!modelsInitialized || isProcessing || isQuitting) + { + return; + } + RunEmbedding(image, imageWidth, imageHeight); + } + + // Check embedding exist + public bool EmbeddingExist() + { + return encoderOutput != null; + } + + // Calculate mask of input image + // image : top bottom format + public void ProcessMask(Color32[] image, int imageWidth, int imageHeight) + { + if (!modelsInitialized || isProcessing || isQuitting) + { + return; + } + + try + { + isProcessing = true; + + // Set up point coords for inference + float[,] coords = GetClickPoints(imageHeight); + float[] labels = GetPointLabels(); + + string coordsLog = $"Points input ({labels.Length}): "; + for (int i = 0; i < labels.Length; i += 1) + { + coordsLog += $"({coords[i, 0]},{-coords[i, 1] - imageHeight + 1})[{labels[i]}]"; + } + + var (masks, scores) = RunInference(imageWidth, imageHeight, coords, labels); + + if (isQuitting) + { + return; + } + + if (masks != null && masks.Length > 0 && scores != null && scores.Length > 0) + { + // Find best mask + int bestMaskIndex = 0; + float maxScore = float.MinValue; + for (int i = 0; i < scores.Length; i++) + { + if (scores[i] > maxScore) + { + maxScore = scores[i]; + bestMaskIndex = i; + } + } + + // TODO: remove for visualisation + if (visualizedResult != null) + { + GameObject.Destroy(visualizedResult); + } + + visualizedResult = CreateMaskedImage( + masks[bestMaskIndex], + image, + imageWidth, + imageHeight + ); + + // Only draw click points if the showClickPoints flag is enabled + if (showClickPoints) + { + visualizedResult = DrawClickPoints(coords, labels, visualizedResult); + } + + if (saveFrame) + { + SaveFrameAsPNG(visualizedResult); + } + + success = true; + } + else + { + //Debug.LogWarning($"No valid masks"); + visualizedResult = CreateEmptyMaskedImage(image, imageWidth, imageHeight); + success = true; + } + } + catch (OperationCanceledException) + { + // Silent cancellation + success = false; + } + catch (Exception e) + { + Debug.LogError($"Error in ProcessCurrentFrame: {e.Message}\n{e.StackTrace}"); + success = false; + } + finally + { + isProcessing = false; + } + } + + private string CreateOutputDirectory() + { + try + { + // Create base directory using Application.persistentDataPath for cross-platform support + string directory = System.IO.Path.Combine(Application.persistentDataPath, "ailiaSAM1"); + + if (!System.IO.Directory.Exists(directory)) + { + System.IO.Directory.CreateDirectory(directory); + Debug.Log($"Created output directory: {directory}"); + } + + return directory; + } + catch (Exception e) + { + Debug.LogError($"Failed to create output directory: {e.Message}"); + } + + return Application.persistentDataPath; + } + + private void SaveFrameAsPNG(Texture2D texture) + { + try + { + string fileNamePrefix = "output"; + // Create path to output directory + string directory = System.IO.Path.Combine( + Application.persistentDataPath, + CreateOutputDirectory() + ); + + // Ensure directory exists + if (!System.IO.Directory.Exists(directory)) + { + System.IO.Directory.CreateDirectory(directory); + } + + // Generate filename with frame number and optional timestamp + string fileName = $"{fileNamePrefix}.png"; + + // Full path to file + string filePath = System.IO.Path.Combine(directory, fileName); + + // Convert texture to PNG bytes + byte[] bytes = texture.EncodeToPNG(); + + // Save synchronously to ensure completion + System.IO.File.WriteAllBytes(filePath, bytes); + + Debug.Log($"Saved output to {fileName}"); + } + catch (Exception e) + { + Debug.LogError($"Error saving output: {e.Message}\n{e.StackTrace}"); + } + } + + public void Destroy() + { + encoder.Close(); + decoder.Close(); + } + + public string EnvironmentName() + { + return encoder.EnvironmentName(); + } +} diff --git a/Assets/AXIP/AILIA-MODELS/ImageSegmentation2/SegmentAnything2Model.cs.meta b/Assets/AXIP/AILIA-MODELS/ImageSegmentation2/SegmentAnything2Model.cs.meta new file mode 100644 index 00000000..f9048523 --- /dev/null +++ b/Assets/AXIP/AILIA-MODELS/ImageSegmentation2/SegmentAnything2Model.cs.meta @@ -0,0 +1,11 @@ +fileFormatVersion: 2 +guid: 3e2f283a42dd549d08dca69966687c1c +MonoImporter: + externalObjects: {} + serializedVersion: 2 + defaultReferences: [] + executionOrder: 0 + icon: {instanceID: 0} + userData: + assetBundleName: + assetBundleVariant: diff --git a/Assets/AXIP/AILIA-MODELS/ImageSegmentation2/Segmentation2Model.cs b/Assets/AXIP/AILIA-MODELS/ImageSegmentation2/Segmentation2Model.cs new file mode 100644 index 00000000..cc21c51b --- /dev/null +++ b/Assets/AXIP/AILIA-MODELS/ImageSegmentation2/Segmentation2Model.cs @@ -0,0 +1,391 @@ +/* AILIA Unity Plugin Segment Sample */ +/* Copyright 2025 AXELL CORPORATION and ax Inc. */ + +using ailia; +using ailiaSDK; +using System; +using System.Collections; +using System.Collections.Generic; +using System.IO; +using System.Linq; +using System.Runtime.CompilerServices; +using System.Text; +using System.Threading; +using System.Threading.Tasks; +using UnityEngine; + +public class Segmentation2Model +{ + private AiliaModel ailiaModel; + + int InputWidth; + int InputHeight; + int InputChannel; + int OutputWidth; + int OutputHeight; + int OutputChannel; + float[] output; + float[] input; + Color32[] outputImage; + Color32[] colorPalette = AiliaImageUtil.CreatePalette(256, 127); + + public List GetModelURLs(ImageSegmentaion2Models modelType) + { + string serverFolderName = ""; + string prototxtName = ""; + string onnxName = ""; + // switch (modelType) + // { + // case ImageSegmentaion2Models.HRNetV2_W18_Small_v2: + // serverFolderName = "hrnet"; + // prototxtName = "HRNetV2-W18-Small-v2.onnx.prototxt"; + // onnxName = "HRNetV2-W18-Small-v2.onnx"; + // break; + // case ImageSegmentaion2Models.HRNetV2_W18_Small_v1: + // serverFolderName = "hrnet"; + // prototxtName = "HRNetV2-W18-Small-v1.onnx.prototxt"; + // onnxName = "HRNetV2-W18-Small-v1.onnx"; + // break; + // case ImageSegmentaion2Models.HRNetV2_W48: + // serverFolderName = "hrnet"; + // prototxtName = "HRNetV2-W48.onnx.prototxt"; + // onnxName = "HRNetV2-W48.onnx"; + // break; + // case ImageSegmentaion2Models.hair_segmentation: + // serverFolderName = "hair_segmentation"; + // prototxtName = "hair_segmentation.opt.onnx.prototxt"; + // onnxName = "hair_segmentation.opt.onnx"; + // break; + // case ImageSegmentaion2Models.pspnet_hair_segmentation: + // serverFolderName = "pspnet-hair-segmentation"; + // prototxtName = "pspnet-hair-segmentation.onnx.prototxt"; + // onnxName = "pspnet-hair-segmentation.onnx"; + // break; + // case ImageSegmentaion2Models.deeplabv3: + // serverFolderName = "deeplabv3"; + // prototxtName = "deeplabv3.opt.onnx.prototxt"; + // onnxName = "deeplabv3.opt.onnx"; + // break; + // case ImageSegmentaion2Models.u2net: + // serverFolderName = "u2net"; + // prototxtName = "u2net_opset11.onnx.prototxt"; + // onnxName = "u2net_opset11.onnx"; + // break; + // case ImageSegmentaion2Models.modnet: + // serverFolderName = "modnet"; + // prototxtName = "modnet.opt.onnx.prototxt"; + // onnxName = "modnet.opt.onnx"; + // break; + // } + + List urlList = new List(); + urlList.Add( + new ModelDownloadURL() { folder_path = serverFolderName, file_name = prototxtName } + ); + urlList.Add( + new ModelDownloadURL() { folder_path = serverFolderName, file_name = onnxName } + ); + return urlList; + } + + public bool InitializeModels(ImageSegmentaion2Models modelType, bool gpuMode) + { + List urlList = GetModelURLs(modelType); + string asset_path = Application.temporaryCachePath; + string prototxtName = urlList[0].file_name; + string onnxName = urlList[1].file_name; + + ailiaModel = new AiliaModel(); + if (gpuMode) + { + // call before OpenFile + ailiaModel.Environment(Ailia.AILIA_ENVIRONMENT_TYPE_GPU); + } + return ailiaModel.OpenFile(asset_path + "/" + prototxtName, asset_path + "/" + onnxName); + } + + private void SetInputShape( + ImageSegmentaion2Models ImageSegmentaion2Models, + int imageWidth, + int imageHeight + ) + { + Ailia.AILIAShape shape = null; + // switch (ImageSegmentaion2Models) + // { + // case ImageSegmentaion2Models.HRNetV2_W18_Small_v2: + // case ImageSegmentaion2Models.HRNetV2_W18_Small_v1: + // case ImageSegmentaion2Models.HRNetV2_W48: + // case ImageSegmentaion2Models.pspnet_hair_segmentation: + // case ImageSegmentaion2Models.deeplabv3: + // shape = ailiaModel.GetInputShape(); + // InputWidth = (int)shape.x; + // InputHeight = (int)shape.y; + // InputChannel = (int)shape.z; + // shape = ailiaModel.GetOutputShape(); + // OutputWidth = (int)shape.x; + // OutputHeight = (int)shape.y; + // OutputChannel = (int)shape.z; + // break; + + // case ImageSegmentaion2Models.hair_segmentation: + // shape = new Ailia.AILIAShape(); + // shape.x = 3; + // shape.y = (uint)imageWidth; + // shape.z = (uint)imageHeight; + // shape.w = 1; + // shape.dim = 4; + // ailiaModel.SetInputShape(shape); + // InputWidth = imageWidth; + // InputHeight = imageHeight; + // InputChannel = 3; + // OutputWidth = imageWidth; + // OutputHeight = imageHeight; + // OutputChannel = 1; + // break; + + // case ImageSegmentaion2Models.u2net: + // shape = ailiaModel.GetInputShape(); + // InputWidth = (int)shape.x; + // InputHeight = (int)shape.y; + // InputChannel = (int)shape.z; + // shape = ailiaModel.GetOutputShape(); + // OutputWidth = (int)shape.x; + // OutputHeight = (int)shape.y; + // OutputChannel = (int)shape.z; + // break; + + // case ImageSegmentaion2Models.modnet: + // shape = new Ailia.AILIAShape(); + // shape.x = (uint)imageWidth / 32 * 32; + // shape.y = (uint)imageHeight / 32 * 32; + // shape.z = 3; + // shape.w = 1; + // shape.dim = 4; + // ailiaModel.SetInputShape(shape); + // InputWidth = imageWidth / 32 * 32; + // InputHeight = imageHeight / 32 * 32; + // InputChannel = 3; + // shape = ailiaModel.GetOutputShape(); + // OutputWidth = (int)shape.x; + // OutputHeight = (int)shape.y; + // OutputChannel = (int)shape.z; + // Debug.Log("" + OutputChannel + "/" + OutputWidth + "/" + OutputHeight); + // //OutputWidth = AiliaImageSource.Width/32*32; + // //OutputHeight = AiliaImageSource.Height/32*32; + // //OutputChannel = 1; + // break; + // } + } + + public void AllocateInputAndOutputTensor( + ImageSegmentaion2Models ImageSegmentaion2Models, + int imageWidth, + int imageHeight + ) + { + SetInputShape(ImageSegmentaion2Models, imageWidth, imageHeight); + input = new float[InputWidth * InputHeight * InputChannel]; + output = new float[OutputWidth * OutputHeight * OutputChannel]; + outputImage = new Color32[OutputWidth * OutputHeight]; + } + + public bool ProcessFrame( + ImageSegmentaion2Models ImageSegmentaion2Models, + Color32[] inputImage, + int inputImageWidth, + int inputImageHeight + ) + { + inputImage = ResizeImage( + inputImage, + inputImageWidth, + inputImageHeight, + InputWidth, + InputHeight + ); + InputDataProcessing(ImageSegmentaion2Models, inputImage, input); + return ailiaModel.Predict(output, input); + } + + public (Color32[], int, int) PostProcesss( + ImageSegmentaion2Models ImageSegmentaion2Models, + int inputImageWidth, + int inputImageHeight + ) + { + // if (ImageSegmentaion2Models == ImageSegmentaion2Models.hair_segmentation) + // LabelPaintHairSegmentation(output, outputImage, Color.red); + // else if (ImageSegmentaion2Models == ImageSegmentaion2Models.pspnet_hair_segmentation) + // LabelPaintPspnet(output, outputImage, Color.red); + // else if ( + // ImageSegmentaion2Models == ImageSegmentaion2Models.u2net + // || ImageSegmentaion2Models == ImageSegmentaion2Models.modnet + // ) + // LabelPaintU2netModnet(output, outputImage, Color.green); + // else + LabelPaint(output, outputImage, OutputChannel, colorPalette); + + Color32[] resizedOutputImage = ResizeImage( + outputImage, + OutputWidth, + OutputHeight, + inputImageWidth, + inputImageHeight + ); + + return (resizedOutputImage, inputImageWidth, inputImageHeight); + } + + Color32[] ResizeImage( + Color32[] inputImage, + int tex_width, + int tex_height, + int InputWidth, + int InputHeight + ) + { + Color32[] outputImage = new Color32[InputWidth * InputHeight]; + for (int y = 0; y < InputHeight; y++) + { + for (int x = 0; x < InputWidth; x++) + { + int x2 = x * tex_width / InputWidth; + int y2 = y * tex_height / InputHeight; + outputImage[y * InputWidth + x] = inputImage[y2 * tex_width + x2]; + } + } + return outputImage; + } + + void InputDataProcessing( + ImageSegmentaion2Models ImageSegmentaion2Models, + Color32[] inputImage, + float[] processedInputBuffer + ) + { + float weight = 1f / 255f; + float bias = 0; + bool rgbRepeats = false; + // switch (ImageSegmentaion2Models) + // { + // case ImageSegmentaion2Models.hair_segmentation: + // rgbRepeats = true; + // break; + // case ImageSegmentaion2Models.pspnet_hair_segmentation: + // InputDataProcessing_PSP(inputImage, processedInputBuffer); + // return; + // case ImageSegmentaion2Models.deeplabv3: + // weight = 1f / 127.5f; + // bias = -1; + // break; + // case ImageSegmentaion2Models.modnet: + // weight = 1f / 127.5f; + // bias = -1; + // break; + // default: + // break; + // } + + // flatten input data + if (rgbRepeats) + { + for (int i = 0; i < inputImage.Length; i++) + { + // rgbrgbrgb... + processedInputBuffer[i * 3 + 0] = (inputImage[i].r) * weight + bias; + processedInputBuffer[i * 3 + 1] = (inputImage[i].g) * weight + bias; + processedInputBuffer[i * 3 + 2] = (inputImage[i].b) * weight + bias; + } + } + else + { + for (int i = 0; i < inputImage.Length; i++) + { + // rrr...ggg...bbb... + processedInputBuffer[i + inputImage.Length * 0] = (inputImage[i].r) * weight + bias; + processedInputBuffer[i + inputImage.Length * 1] = (inputImage[i].g) * weight + bias; + processedInputBuffer[i + inputImage.Length * 2] = (inputImage[i].b) * weight + bias; + } + } + } + + void InputDataProcessing_PSP(Color32[] inputImage, float[] processedInputBuffer) + { + for (int i = 0; i < inputImage.Length; i++) + { + // rrr...ggg...bbb... + processedInputBuffer[i + inputImage.Length * 0] = + (inputImage[i].r * (1f / 255f) - 0.485f) * (1f / 0.229f); + processedInputBuffer[i + inputImage.Length * 1] = + (inputImage[i].g * (1f / 255f) - 0.456f) * (1f / 0.224f); + processedInputBuffer[i + inputImage.Length * 2] = + (inputImage[i].b * (1f / 255f) - 0.406f) * (1f / 0.225f); + } + } + + void LabelPaint(float[] labelData, Color32[] pixelBuffer, int channel, Color32[] palette) + { + Debug.Assert(palette.Length >= channel, "wrong palette size"); + Debug.Assert(labelData.Length == pixelBuffer.Length * channel, "wrong parameter"); + + for (int i = 0; i < pixelBuffer.Length; i++) + { + int maxIndex = 0; + float maxValue = labelData[i + 0 * (pixelBuffer.Length)]; + for (int c = 1; c < channel; c++) + { + if (maxValue < labelData[i + c * pixelBuffer.Length]) + { + maxValue = labelData[i + c * pixelBuffer.Length]; + maxIndex = c; + } + } + pixelBuffer[i] = palette[maxIndex]; + } + } + + void LabelPaintHairSegmentation(float[] labelData, Color32[] pixelBuffer, Color32 color) + { + Debug.Assert(labelData.Length == pixelBuffer.Length, "wrong parameter"); + + for (int i = 0; i < pixelBuffer.Length; i++) + { + pixelBuffer[i] = color; + pixelBuffer[i].a = (byte)(Mathf.Clamp01(labelData[i]) * 255); + } + } + + void LabelPaintPspnet(float[] labelData, Color32[] pixelBuffer, Color32 color) + { + Debug.Assert(labelData.Length == pixelBuffer.Length, "wrong parameter"); + + for (int i = 0; i < pixelBuffer.Length; i++) + { + pixelBuffer[i] = color; + + float k = Mathf.Exp(labelData[i]); + pixelBuffer[i].a = (byte)(k / (1.0f + k) * 255); + } + } + + void LabelPaintU2netModnet(float[] labelData, Color32[] pixelBuffer, Color32 color) + { + Debug.Assert(labelData.Length == pixelBuffer.Length, "wrong parameter"); + for (int i = 0; i < pixelBuffer.Length; i++) + { + pixelBuffer[i] = color; + pixelBuffer[i].a = (byte)(255 - Mathf.Clamp01(labelData[i]) * 255); + } + } + + public void Destroy() + { + ailiaModel?.Close(); + } + + public string EnvironmentName() + { + return ailiaModel.EnvironmentName(); + } +} diff --git a/Assets/AXIP/AILIA-MODELS/ImageSegmentation2/Segmentation2Model.cs.meta b/Assets/AXIP/AILIA-MODELS/ImageSegmentation2/Segmentation2Model.cs.meta new file mode 100644 index 00000000..448898a4 --- /dev/null +++ b/Assets/AXIP/AILIA-MODELS/ImageSegmentation2/Segmentation2Model.cs.meta @@ -0,0 +1,11 @@ +fileFormatVersion: 2 +guid: 792762c74ff014b5597497355b65b6cd +MonoImporter: + externalObjects: {} + serializedVersion: 2 + defaultReferences: [] + executionOrder: 0 + icon: {instanceID: 0} + userData: + assetBundleName: + assetBundleVariant: From c0ca8570a80c4e6990b068ade9770a3a0b089c68 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?=E3=82=AD=E3=83=A7=E3=83=BB=E3=83=AA=E3=83=BC=E3=82=B7?= =?UTF-8?q?=E3=83=A5=E3=83=B3?= Date: Mon, 16 Jun 2025 14:37:04 +0900 Subject: [PATCH 02/16] Update error handling --- .../SegmentAnything2Model.cs | 420 +++++------------- 1 file changed, 101 insertions(+), 319 deletions(-) diff --git a/Assets/AXIP/AILIA-MODELS/ImageSegmentation2/SegmentAnything2Model.cs b/Assets/AXIP/AILIA-MODELS/ImageSegmentation2/SegmentAnything2Model.cs index f62760c9..79e08162 100644 --- a/Assets/AXIP/AILIA-MODELS/ImageSegmentation2/SegmentAnything2Model.cs +++ b/Assets/AXIP/AILIA-MODELS/ImageSegmentation2/SegmentAnything2Model.cs @@ -301,9 +301,7 @@ private void RunEmbedding(Color32[] image, int imgWidth, int imgHeight) } float[,,,] inputTensor = PreprocessImage(image, imgWidth, imgHeight, targetSize); - // var (inputData, inputSize) = PreprocessImage2(image, imgWidth, imgHeight); float[] nchw = Flatten4D(inputTensor); - // float[] nchw = inputData; try { @@ -335,7 +333,7 @@ private void RunEmbedding(Color32[] image, int imgWidth, int imgHeight) // Run encoder bool encResult = encoder.Update(); - if (isQuitting || encoder == null || decoder == null) + if (isQuitting || encoder == null) { return; } @@ -593,7 +591,6 @@ private void RunEmbedding(Color32[] image, int imgWidth, int imgHeight) ]; encoderOutput = Flatten4D(lastFeatElement); - Debug.Log("encoderOutput"); highResFeats = new float[featsArray.Length - 1][]; for (int i = 0; i < allButLast.Length; i++) { @@ -1149,10 +1146,22 @@ float[] pointLabels (uint)promptMasksEnabledIndex ); + if ( + !concatPointShapeResult + || !labelsShapeResult + || !masksShapeResult + || !masksEnabledShapeResult + ) + { + Debug.LogError("Failed to set input blob shapes"); + return (new bool[0][,], new float[0]); + } + for (int i = 0; i < flattenedCoords.Length; i++) { Debug.Log(flattenedCoords[i]); } + bool setCoordsResult = prompt.SetInputBlobData( flattenedCoords, (uint)promptCoordsIndex @@ -1167,9 +1176,9 @@ float[] pointLabels (uint)promptMasksEnabledIndex ); - if (!setCoordsResult || !setlabelsResult || !masksEnabledShapeResult) + if (!setCoordsResult || !setlabelsResult || !setMaskseResult || !setMasksEnabledResult) { - Debug.LogError("Failed to set required common blob indices"); + Debug.LogError("Failed to set blob data"); return (new bool[0][,], new float[0]); } @@ -1193,11 +1202,6 @@ float[] pointLabels return (new bool[0][,], new float[0]); } - if (isQuitting || prompt == null) - { - return (new bool[0][,], new float[0]); - } - int sparseEmbeddingsBlobIndex = prompt.FindBlobIndexByName("sparse_embeddings"); int denseEmbeddingsBlobIndex = prompt.FindBlobIndexByName("dense_embeddings"); int densePeBlobIndex = prompt.FindBlobIndexByName("dense_pe"); @@ -1209,16 +1213,11 @@ float[] pointLabels ) { Debug.LogError( - "Could not find sparse_embeddings, dense_embeddings and dense_pe blobs" + "Could not find sparse_embeddings, dense_embeddings and dense_pe indices" ); return (new bool[0][,], new float[0]); } - if (isQuitting || prompt == null) - { - return (new bool[0][,], new float[0]); - } - // Get blob shapes ailia.Ailia.AILIAShape sparseEmbeddingsBlobShape = prompt.GetBlobShape( (uint)sparseEmbeddingsBlobIndex @@ -1261,6 +1260,24 @@ float[] pointLabels int highResFeatures1Index = decoder.FindBlobIndexByName("high_res_features1"); int highResFeatures2Index = decoder.FindBlobIndexByName("high_res_features2"); + if ( + imageEmbeddingsIndex < 0 + || imagePeIndex < 0 + || sparsePromptEmbeddingsIndex < 0 + || densePromptEmbeddingsIndex < 0 + || highResFeatures1Index < 0 + || highResFeatures2Index < 0 + ) + { + Debug.LogError("Could not find required indices"); + return (new bool[0][,], new float[0]); + } + + if (isQuitting || decoder == null) + { + return (new bool[0][,], new float[0]); + } + ailia.Ailia.AILIAShape imageEmbeddingsShape = new ailia.Ailia.AILIAShape(); imageEmbeddingsShape.dim = 4; imageEmbeddingsShape.w = 1; // batch=1 @@ -1302,17 +1319,6 @@ float[] pointLabels highResFeatures2Shape.y = 128; // height=64 highResFeatures2Shape.x = 128; // width=64 - if (imageEmbeddingsIndex < 0 || imagePeIndex < 0) - { - Debug.LogError("Could not find mask and score blobs"); - return (new bool[0][,], new float[0]); - } - - if (isQuitting || decoder == null) - { - return (new bool[0][,], new float[0]); - } - bool imageEmbeddingsShapeResult = decoder.SetInputBlobShape( imageEmbeddingsShape, (uint)imageEmbeddingsIndex @@ -1340,6 +1346,24 @@ float[] pointLabels (uint)highResFeatures2Index ); + if ( + !imageEmbeddingsShapeResult + || !imagePeShapeResult + || !sparsePromptEmbeddingsShapeResult + || !densePromptEmbeddingsShapeResult + || !highResFeatures1ShapeResult + || !highResFeatures2ShapeResult + ) + { + Debug.LogError("Failed to set input blob shapes"); + return (new bool[0][,], new float[0]); + } + + if (isQuitting || decoder == null) + { + return (new bool[0][,], new float[0]); + } + bool imageEmbeddingsResult = decoder.SetInputBlobData( encoderOutput, (uint)imageEmbeddingsIndex @@ -1367,6 +1391,24 @@ float[] pointLabels (uint)highResFeatures2Index ); + if ( + !imageEmbeddingsResult + || !imagePeResult + || !sparseEmbeddingsResult + || !denseEmbeddingsResult + || !highResFeatures1Result + || !highResFeatures2Result + ) + { + Debug.LogError("Failed to set input blob data"); + return (new bool[0][,], new float[0]); + } + + if (isQuitting || decoder == null) + { + return (new bool[0][,], new float[0]); + } + // Run decoder bool decoderResult = decoder.Update(); @@ -1393,6 +1435,23 @@ float[] pointLabels int iouPredBlobIndex = decoder.FindBlobIndexByName("iou_pred"); int samTokensOutBlobIndex = decoder.FindBlobIndexByName("sam_tokens_out"); int objectScoreLogitsBlobIndex = decoder.FindBlobIndexByName("object_score_logits"); + + if ( + masksBlobIndex < 0 + || iouPredBlobIndex < 0 + || samTokensOutBlobIndex < 0 + || objectScoreLogitsBlobIndex < 0 + ) + { + Debug.LogError("Could not find required indices"); + return (new bool[0][,], new float[0]); + } + + if (isQuitting || decoder == null) + { + return (new bool[0][,], new float[0]); + } + ailia.Ailia.AILIAShape masksBlobShape = decoder.GetBlobShape((uint)masksBlobIndex); float[] masksBlobOutput = new float[ masksBlobShape.w * masksBlobShape.z * masksBlobShape.y * masksBlobShape.x @@ -1430,6 +1489,17 @@ float[] pointLabels (uint)objectScoreLogitsBlobIndex ); + if ( + !getMasksBlobResult + || !getiouPredBlobResult + || !getsamTokensBlobResult + || !objectScoreLogitsBlobResult + ) + { + Debug.LogError("Failed to get blob data"); + return (new bool[0][,], new float[0]); + } + float[,,,] masks = ReshapeTo4D( masksBlobOutput, (int)masksBlobShape.w, @@ -1454,30 +1524,6 @@ float[] pointLabels (int)objectScoreLogitsBlobShape.y, (int)objectScoreLogitsBlobShape.x ); - // masks = masks[:, 1:, :, :] 1 - // float[,,,] lowResMasks = SliceChannelDim(masks); - // iou_pred = iou_pred[:, 1:] 2 - // iouPred = Slice2DColumns(iouPred, 1); - // sam_tokens_out = mask_tokens_out[:, 1:] - // samTokens = Slice3D_Dim1_From1(samTokens, 1); - // masks = self.postprocess_masks( - // low_res_masks, orig_hw - // ) - // float[,,,] resized = PostprocessMasks(lowResMasks, new int[] { imgHeight, imgWidth }); - // low_res_masks 3 - // Clip(ref lowResMasks, -32.0f, -32.0f); - // float maskThreshold = 0.0f; - // 1 - // bool[,,,] binaryMask = ThresholdMask(resized, maskThreshold); - - // sorted_ind = np.argsort(scores)[::-1] - // int[] sortedInd = ArgsortDescending(iouPred); - - // bool[,,,] newMasks = ReorderMasks(binaryMask, sortedInd); - - // bool[][,] masksResult = new bool[1][,]; - // masksResult[0] = PostprocessMask(resized, imgHeight, imgWidth); - // Debug.Log(iouPred[0, 0]); if (isQuitting || decoder == null) { @@ -1485,17 +1531,14 @@ float[] pointLabels } int numMasks = (int)iouPredBlobShape.x; - // Debug.Log(numMasks); int maskWidth = (int)masksBlobShape.x; int maskHeight = (int)masksBlobShape.y; int maskArea = maskWidth * maskHeight; bool[][,] masksResult = new bool[numMasks][,]; - // Debug.Log(maskWidth); - // Debug.Log(maskHeight); - // Debug.Log(maskArea); - // Debug.Log(masksBlobOutput.Length); - // float[] maskUpscaled = ResizeMask1D(masksBlobOutput, maskHeight, maskWidth, imgHeight, imgWidth); + Debug.Log(maskWidth); + Debug.Log(maskHeight); + Debug.Log(maskArea); for (int i = 0; i < numMasks; i++) { @@ -1518,190 +1561,6 @@ float[] pointLabels } } - // private bool[,,,] ReorderMasks(bool[,,,] masks, int[] sortedInd) - // { - // int n = sortedInd.Length; - // int c = masks.GetLength(1); - // int h = masks.GetLength(2); - // int w = masks.GetLength(3); - - // bool[,,,] reordered = new bool[n, c, h, w]; - - // for (int i = 0; i < n; i++) - // { - // int srcIndex = sortedInd[i]; - // for (int j = 0; j < c; j++) - // for (int y = 0; y < h; y++) - // for (int x = 0; x < w; x++) - // reordered[i, j, y, x] = masks[srcIndex, j, y, x]; - // } - - // return reordered; - // } - - // private int[] ArgsortDescending(float[,] scores) - // { - // int rows = scores.GetLength(0); - // int cols = scores.GetLength(1); - // int total = rows * cols; - - // // Create index-value pairs - // var indexed = new List<(int index, float value)>(total); - // for (int i = 0; i < rows; i++) - // for (int j = 0; j < cols; j++) - // indexed.Add((i * cols + j, scores[i, j])); - - // // Sort descending by value - // var sorted = indexed.OrderByDescending(x => x.value).Select(x => x.index).ToArray(); - - // return sorted; - // } - - // private float[] ResizeMask1D(float[] input, int inH, int inW, int outH, int outW) - // { - // float[] output = new float[outH * outW]; - // float yScale = (float)inH / outH; - // float xScale = (float)inW / outW; - - // for (int y = 0; y < outH; y++) - // { - // float inY = y * yScale; - // int y0 = (int)Math.Floor(inY); - // int y1 = Math.Min(y0 + 1, inH - 1); - // float yLerp = inY - y0; - - // for (int x = 0; x < outW; x++) - // { - // float inX = x * xScale; - // int x0 = (int)Math.Floor(inX); - // int x1 = Math.Min(x0 + 1, inW - 1); - // float xLerp = inX - x0; - - // // Get pixel values - // float v00 = input[y0 * inW + x0]; - // float v01 = input[y0 * inW + x1]; - // float v10 = input[y1 * inW + x0]; - // float v11 = input[y1 * inW + x1]; - - // float top = (1 - xLerp) * v00 + xLerp * v01; - // float bottom = (1 - xLerp) * v10 + xLerp * v11; - // float value = (1 - yLerp) * top + yLerp * bottom; - - // output[y * outW + x] = value; - // } - // } - - // return output; - // } - - // private void Clip(ref float[,,,] array, float minValue, float maxValue) - // { - // int d0 = array.GetLength(0); - // int d1 = array.GetLength(1); - // int d2 = array.GetLength(2); - // int d3 = array.GetLength(3); - - // for (int i0 = 0; i0 < d0; i0++) - // for (int i1 = 0; i1 < d1; i1++) - // for (int i2 = 0; i2 < d2; i2++) - // for (int i3 = 0; i3 < d3; i3++) - // { - // if (array[i0, i1, i2, i3] < minValue) - // array[i0, i1, i2, i3] = minValue; - // else if (array[i0, i1, i2, i3] > maxValue) - // array[i0, i1, i2, i3] = maxValue; - // } - // } - - // private bool[,,,] ThresholdMask(float[,,,] input, float threshold) - // { - // int d0 = input.GetLength(0); - // int d1 = input.GetLength(1); - // int d2 = input.GetLength(2); - // int d3 = input.GetLength(3); - - // bool[,,,] mask = new bool[d0, d1, d2, d3]; - - // for (int i0 = 0; i0 < d0; i0++) - // for (int i1 = 0; i1 < d1; i1++) - // for (int i2 = 0; i2 < d2; i2++) - // for (int i3 = 0; i3 < d3; i3++) - // mask[i0, i1, i2, i3] = input[i0, i1, i2, i3] > threshold; - - // return mask; - // } - - // private float[,,,] PostprocessMasks(float[,,,] masks, int[] origHW) - // { - // int N = masks.GetLength(0); - // int C = masks.GetLength(1); - // int H = masks.GetLength(2); - // int W = masks.GetLength(3); - - // int newH = origHW[0]; - // int newW = origHW[1]; - // float[,,,] output = new float[N, C, newH, newW]; - - // for (int n = 0; n < N; n++) - // { - // for (int c = 0; c < C; c++) - // { - // // Extract [H, W] slice for mask[n, c] - // float[,] src = new float[H, W]; - // for (int h = 0; h < H; h++) - // for (int w = 0; w < W; w++) - // src[h, w] = masks[n, c, h, w]; - - // // Resize using bilinear interpolation - // float[,] resized = ResizeBilinear(src, newH, newW); - - // // Store into output[n, c] - // for (int h = 0; h < newH; h++) - // for (int w = 0; w < newW; w++) - // output[n, c, h, w] = resized[h, w]; - // } - // } - - // return output; - // } - - // private float[,,,] SliceChannelDim(float[,,,] input) - // { - // int N = input.GetLength(0); - // int C = input.GetLength(1); - // int H = input.GetLength(2); - // int W = input.GetLength(3); - - // float[,,,] result = new float[N, C - 1, H, W]; - - // for (int n = 0; n < N; n++) - // for (int c = 1; c < C; c++) // start at 1 - // for (int h = 0; h < H; h++) - // for (int w = 0; w < W; w++) - // result[n, c - 1, h, w] = input[n, c, h, w]; - - // return result; - // } - - // private float[,,] Slice3D_Dim1_From1(float[,,] input, int start) - // { - // int D0 = input.GetLength(0); // A - // int D1 = input.GetLength(1); // B - // int D2 = input.GetLength(2); // C - - // if (start >= D1) - // throw new ArgumentException("Start index is out of bounds for axis 1"); - - // float[,,] output = new float[D0, D1 - start, D2]; - - // for (int i = 0; i < D0; i++) - // for (int j = 1; j < D1; j++) - // for (int k = 0; k < D2; k++) - // output[i, j - start, k] = input[i, j, k]; - - // return output; - // } - private float[,] ReshapeTo2D(float[] flat, int rows, int cols) { if (flat.Length != rows * cols) @@ -1716,24 +1575,6 @@ float[] pointLabels return result; } - // private float[,] Slice2DColumns(float[,] input, int startCol) - // { - // int rows = input.GetLength(0); - // int cols = input.GetLength(1); - - // if (startCol >= cols) - // throw new ArgumentException("startCol is out of range."); - - // int newCols = cols - startCol; - // float[,] result = new float[rows, newCols]; - - // for (int r = 0; r < rows; r++) - // for (int c = 0; c < newCols; c++) - // result[r, c] = input[r, c + startCol]; - - // return result; - // } - // Helper to convert 1D array to 4D array private float[,,,] ReshapeToTensor(float[] data, int maskIndex, int height, int width, int area) { @@ -1894,65 +1735,6 @@ private float GetScale(int texWidth, int texHeight) return targetSize / (float)Mathf.Max(texWidth, texHeight); } - // Preprocess image for model input - private (float[], ValueTuple) PreprocessImage2( - Color32[] camera, - int texWidth, - int texHeight - ) - { - // Create CHW layout data array (channel, height, width) - float[] normalizedData = new float[3 * targetSize * targetSize]; - - // Optimize by computing constants outside the inner loop - int ch0Offset = 0; - int ch1Offset = targetSize * targetSize; - int ch2Offset = 2 * targetSize * targetSize; - - float scale = GetScale(texWidth, texHeight); - - // Fill with normalized values and padding - for (int y = 0; y < targetSize; y++) - { - for (int x = 0; x < targetSize; x++) - { - float fx = x / scale; - float fy = y / scale; - Color32 v = Bilinear(camera, texWidth, texHeight, fx, fy); - - int baseIdx = y * targetSize + x; // Top2Bottom - - normalizedData[ch0Offset + baseIdx] = (v.r / 255.0f - Mean[0]) / Std[0]; - normalizedData[ch1Offset + baseIdx] = (v.g / 255.0f - Mean[1]) / Std[1]; - normalizedData[ch2Offset + baseIdx] = (v.b / 255.0f - Mean[2]) / Std[2]; - } - } - - return (normalizedData, (texHeight, texWidth)); - } - - private Color32 Bilinear(Color32[] face, int w, int h, float fx, float fy) - { - // Debug.Log("Bilinear"); - int x2 = (int)fx; - int y2 = (int)fy; - float xa = 1.0f - (fx - x2); - float xb = 1.0f - xa; - float ya = 1.0f - (fy - y2); - float yb = 1.0f - ya; - if (x2 >= w || y2 >= h || x2 < 0 || y2 < 0){ - return new Color32(0, 0, 0, 255); - } - Color32 c1 = face[y2 * w + x2]; - Color32 c2 = (x2+1 < w) ? face[y2 * w + x2 + 1] : c1; - Color32 c3 = (y2+1 < h) ? face[(y2 + 1) * w + x2] : c1; - Color32 c4 = (x2+1 < w && y2+1 < h) ? face[(y2 + 1) * w + x2 + 1] : c1; - byte r = (byte)(c1.r * xa * ya + c2.r * xb * ya + c3.r * xa * yb + c4.r * xb * yb); - byte g = (byte)(c1.g * xa * ya + c2.g * xb * ya + c3.g * xa * yb + c4.g * xb * yb); - byte b = (byte)(c1.b * xa * ya + c2.b * xb * ya + c3.b * xa * yb + c4.b * xb * yb); - return new Color32(r, g, b, 255); - } - private float[,,,] PreprocessImage( Color32[] inputImage, int originalWidth, From f4e68c041f176c083bf63249f24c1bc6e0787cb3 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?=E3=82=AD=E3=83=A7=E3=83=BB=E3=83=AA=E3=83=BC=E3=82=B7?= =?UTF-8?q?=E3=83=A5=E3=83=B3?= Date: Mon, 16 Jun 2025 15:27:55 +0900 Subject: [PATCH 03/16] Clean up codes --- .../AiliaImageSegmentation2Sample.cs | 96 +++---------------- .../ImageSegmentation2Sample.unity | 8 +- 2 files changed, 14 insertions(+), 90 deletions(-) diff --git a/Assets/AXIP/AILIA-MODELS/ImageSegmentation2/AiliaImageSegmentation2Sample.cs b/Assets/AXIP/AILIA-MODELS/ImageSegmentation2/AiliaImageSegmentation2Sample.cs index 9789ce76..6e5418b6 100644 --- a/Assets/AXIP/AILIA-MODELS/ImageSegmentation2/AiliaImageSegmentation2Sample.cs +++ b/Assets/AXIP/AILIA-MODELS/ImageSegmentation2/AiliaImageSegmentation2Sample.cs @@ -13,14 +13,6 @@ namespace ailiaSDK // Model list public enum ImageSegmentaion2Models { - // HRNetV2_W18_Small_v2, - // HRNetV2_W18_Small_v1, - // HRNetV2_W48, - // hair_segmentation, - // pspnet_hair_segmentation, - // deeplabv3, - // u2net, - // modnet, image_encoder_hiera_l } @@ -45,13 +37,7 @@ public class AiliaImageSegmentation2Sample : MonoBehaviour // Input source AiliaImageSource AiliaImageSource; - public Texture2D image_source_hrnet = null; - public Texture2D image_source_hair_segmentation = null; - public Texture2D image_source_pspnet_hair_segmentation = null; - public Texture2D image_source_deeplabv3 = null; - public Texture2D image_source_u2net = null; - public Texture2D image_source_modnet = null; - public Texture2D image_source_sam1 = null; + public Texture2D image_source_sam2 = null; // Pre-and-Post processing Shader Material blendMaterial; @@ -68,7 +54,6 @@ public class AiliaImageSegmentation2Sample : MonoBehaviour Vector2 rawImageSize; // Segment Anything Model - private Segmentation2Model seg2Model; private SegmentAnything2Model sam2Model; private bool isDraggingForBox = false; private Rect boxRect = new(); @@ -164,14 +149,6 @@ void Update() } if (modelPrepared && !modelAllocated) { - if (ImageSegmentaion2Models != ImageSegmentaion2Models.image_encoder_hiera_l) - { - seg2Model.AllocateInputAndOutputTensor( - ImageSegmentaion2Models, - AiliaImageSource.Width, - AiliaImageSource.Height - ); - } modelAllocated = true; } if (camera_mode && !ailia_camera.IsEnable()) @@ -244,15 +221,6 @@ void Update() sam2Model.ProcessMask(inputImage, inputImageWidth, inputImageHeight); result = sam2Model.success; } - else - { - result = seg2Model.ProcessFrame( - ImageSegmentaion2Models, - inputImage, - inputImageWidth, - inputImageHeight - ); - } if (!result) { @@ -264,20 +232,9 @@ void Update() Color32[] outputImage; int outputWidth, outputHeight; - if (ImageSegmentaion2Models == ImageSegmentaion2Models.image_encoder_hiera_l) - { - outputImage = sam2Model.visualizedResult.GetPixels32(); - outputWidth = sam2Model.visualizedResult.width; - outputHeight = sam2Model.visualizedResult.height; - } - else - { - (outputImage, outputWidth, outputHeight) = seg2Model.PostProcesss( - ImageSegmentaion2Models, - inputImageWidth, - inputImageHeight - ); - } + outputImage = sam2Model.visualizedResult.GetPixels32(); + outputWidth = sam2Model.visualizedResult.width; + outputHeight = sam2Model.visualizedResult.height; long end_time2 = DateTime.UtcNow.Ticks / TimeSpan.TicksPerMillisecond; @@ -346,18 +303,15 @@ void CreateAiliaNet(ImageSegmentaion2Models modelType, bool gpu_mode = true) sam2Model = new SegmentAnything2Model(); urlList = sam2Model.GetModelURLs(ImageSegmentaion2Models); } - else - { - seg2Model = new Segmentation2Model(); - urlList = seg2Model.GetModelURLs(ImageSegmentaion2Models); - } StartCoroutine( ailia_download.DownloadWithProgressFromURL( urlList, () => { - if (ImageSegmentaion2Models == ImageSegmentaion2Models.image_encoder_hiera_l) + if ( + ImageSegmentaion2Models == ImageSegmentaion2Models.image_encoder_hiera_l + ) { modelPrepared = sam2Model.InitializeModels( ImageSegmentaion2Models, @@ -367,11 +321,11 @@ void CreateAiliaNet(ImageSegmentaion2Models modelType, bool gpu_mode = true) } else { - modelPrepared = seg2Model.InitializeModels( - ImageSegmentaion2Models, - gpu_mode - ); - envName = seg2Model.EnvironmentName(); + // modelPrepared = seg2Model.InitializeModels( + // ImageSegmentaion2Models, + // gpu_mode + // ); + // envName = seg2Model.EnvironmentName(); } } ) @@ -385,28 +339,8 @@ AiliaImageSource ailiaImageSource { switch (ImageSegmentaion2Models) { - // case ImageSegmentaion2Models.HRNetV2_W18_Small_v2: - // case ImageSegmentaion2Models.HRNetV2_W18_Small_v1: - // case ImageSegmentaion2Models.HRNetV2_W48: - // ailiaImageSource.CreateSource(image_source_hrnet); - // break; - // case ImageSegmentaion2Models.hair_segmentation: - // ailiaImageSource.CreateSource(image_source_hair_segmentation); - // break; - // case ImageSegmentaion2Models.pspnet_hair_segmentation: - // ailiaImageSource.CreateSource(image_source_pspnet_hair_segmentation); - // break; - // case ImageSegmentaion2Models.deeplabv3: - // ailiaImageSource.CreateSource(image_source_deeplabv3); - // break; - // case ImageSegmentaion2Models.u2net: - // ailiaImageSource.CreateSource(image_source_u2net); - // break; - // case ImageSegmentaion2Models.modnet: - // ailiaImageSource.CreateSource(image_source_modnet); - // break; case ImageSegmentaion2Models.image_encoder_hiera_l: - ailiaImageSource.CreateSource(image_source_sam1); + ailiaImageSource.CreateSource(image_source_sam2); break; } } @@ -559,10 +493,6 @@ void DestroyAiliaDetector() { sam2Model.Destroy(); } - if (seg2Model != null) - { - seg2Model.Destroy(); - } } } } diff --git a/Assets/AXIP/AILIA-MODELS/ImageSegmentation2/ImageSegmentation2Sample.unity b/Assets/AXIP/AILIA-MODELS/ImageSegmentation2/ImageSegmentation2Sample.unity index 3e72687f..fdee49d2 100644 --- a/Assets/AXIP/AILIA-MODELS/ImageSegmentation2/ImageSegmentation2Sample.unity +++ b/Assets/AXIP/AILIA-MODELS/ImageSegmentation2/ImageSegmentation2Sample.unity @@ -256,13 +256,7 @@ MonoBehaviour: UICanvas: {fileID: 2075427421} camera_mode: 0 camera_id: 0 - image_source_hrnet: {fileID: 2800000, guid: ff78b2bc2394948d085a57b0073d1196, type: 3} - image_source_hair_segmentation: {fileID: 0} - image_source_pspnet_hair_segmentation: {fileID: 0} - image_source_deeplabv3: {fileID: 0} - image_source_u2net: {fileID: 0} - image_source_modnet: {fileID: 0} - image_source_sam1: {fileID: 2800000, guid: ff78b2bc2394948d085a57b0073d1196, type: 3} + image_source_sam2: {fileID: 0} --- !u!114 &296455737 MonoBehaviour: m_ObjectHideFlags: 0 From 3872be2e9f34c77a93265841545b66073fe3f012 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?=E3=82=AD=E3=83=A7=E3=83=BB=E3=83=AA=E3=83=BC=E3=82=B7?= =?UTF-8?q?=E3=83=A5=E3=83=B3?= Date: Mon, 16 Jun 2025 15:29:02 +0900 Subject: [PATCH 04/16] Clean up codes --- .../AiliaImageSegmentation2Sample.cs | 8 - .../ImageSegmentation2/Segmentation2Model.cs | 391 ------------------ .../Segmentation2Model.cs.meta | 11 - 3 files changed, 410 deletions(-) delete mode 100644 Assets/AXIP/AILIA-MODELS/ImageSegmentation2/Segmentation2Model.cs delete mode 100644 Assets/AXIP/AILIA-MODELS/ImageSegmentation2/Segmentation2Model.cs.meta diff --git a/Assets/AXIP/AILIA-MODELS/ImageSegmentation2/AiliaImageSegmentation2Sample.cs b/Assets/AXIP/AILIA-MODELS/ImageSegmentation2/AiliaImageSegmentation2Sample.cs index 6e5418b6..2a086904 100644 --- a/Assets/AXIP/AILIA-MODELS/ImageSegmentation2/AiliaImageSegmentation2Sample.cs +++ b/Assets/AXIP/AILIA-MODELS/ImageSegmentation2/AiliaImageSegmentation2Sample.cs @@ -319,14 +319,6 @@ void CreateAiliaNet(ImageSegmentaion2Models modelType, bool gpu_mode = true) ); envName = sam2Model.EnvironmentName(); } - else - { - // modelPrepared = seg2Model.InitializeModels( - // ImageSegmentaion2Models, - // gpu_mode - // ); - // envName = seg2Model.EnvironmentName(); - } } ) ); diff --git a/Assets/AXIP/AILIA-MODELS/ImageSegmentation2/Segmentation2Model.cs b/Assets/AXIP/AILIA-MODELS/ImageSegmentation2/Segmentation2Model.cs deleted file mode 100644 index cc21c51b..00000000 --- a/Assets/AXIP/AILIA-MODELS/ImageSegmentation2/Segmentation2Model.cs +++ /dev/null @@ -1,391 +0,0 @@ -/* AILIA Unity Plugin Segment Sample */ -/* Copyright 2025 AXELL CORPORATION and ax Inc. */ - -using ailia; -using ailiaSDK; -using System; -using System.Collections; -using System.Collections.Generic; -using System.IO; -using System.Linq; -using System.Runtime.CompilerServices; -using System.Text; -using System.Threading; -using System.Threading.Tasks; -using UnityEngine; - -public class Segmentation2Model -{ - private AiliaModel ailiaModel; - - int InputWidth; - int InputHeight; - int InputChannel; - int OutputWidth; - int OutputHeight; - int OutputChannel; - float[] output; - float[] input; - Color32[] outputImage; - Color32[] colorPalette = AiliaImageUtil.CreatePalette(256, 127); - - public List GetModelURLs(ImageSegmentaion2Models modelType) - { - string serverFolderName = ""; - string prototxtName = ""; - string onnxName = ""; - // switch (modelType) - // { - // case ImageSegmentaion2Models.HRNetV2_W18_Small_v2: - // serverFolderName = "hrnet"; - // prototxtName = "HRNetV2-W18-Small-v2.onnx.prototxt"; - // onnxName = "HRNetV2-W18-Small-v2.onnx"; - // break; - // case ImageSegmentaion2Models.HRNetV2_W18_Small_v1: - // serverFolderName = "hrnet"; - // prototxtName = "HRNetV2-W18-Small-v1.onnx.prototxt"; - // onnxName = "HRNetV2-W18-Small-v1.onnx"; - // break; - // case ImageSegmentaion2Models.HRNetV2_W48: - // serverFolderName = "hrnet"; - // prototxtName = "HRNetV2-W48.onnx.prototxt"; - // onnxName = "HRNetV2-W48.onnx"; - // break; - // case ImageSegmentaion2Models.hair_segmentation: - // serverFolderName = "hair_segmentation"; - // prototxtName = "hair_segmentation.opt.onnx.prototxt"; - // onnxName = "hair_segmentation.opt.onnx"; - // break; - // case ImageSegmentaion2Models.pspnet_hair_segmentation: - // serverFolderName = "pspnet-hair-segmentation"; - // prototxtName = "pspnet-hair-segmentation.onnx.prototxt"; - // onnxName = "pspnet-hair-segmentation.onnx"; - // break; - // case ImageSegmentaion2Models.deeplabv3: - // serverFolderName = "deeplabv3"; - // prototxtName = "deeplabv3.opt.onnx.prototxt"; - // onnxName = "deeplabv3.opt.onnx"; - // break; - // case ImageSegmentaion2Models.u2net: - // serverFolderName = "u2net"; - // prototxtName = "u2net_opset11.onnx.prototxt"; - // onnxName = "u2net_opset11.onnx"; - // break; - // case ImageSegmentaion2Models.modnet: - // serverFolderName = "modnet"; - // prototxtName = "modnet.opt.onnx.prototxt"; - // onnxName = "modnet.opt.onnx"; - // break; - // } - - List urlList = new List(); - urlList.Add( - new ModelDownloadURL() { folder_path = serverFolderName, file_name = prototxtName } - ); - urlList.Add( - new ModelDownloadURL() { folder_path = serverFolderName, file_name = onnxName } - ); - return urlList; - } - - public bool InitializeModels(ImageSegmentaion2Models modelType, bool gpuMode) - { - List urlList = GetModelURLs(modelType); - string asset_path = Application.temporaryCachePath; - string prototxtName = urlList[0].file_name; - string onnxName = urlList[1].file_name; - - ailiaModel = new AiliaModel(); - if (gpuMode) - { - // call before OpenFile - ailiaModel.Environment(Ailia.AILIA_ENVIRONMENT_TYPE_GPU); - } - return ailiaModel.OpenFile(asset_path + "/" + prototxtName, asset_path + "/" + onnxName); - } - - private void SetInputShape( - ImageSegmentaion2Models ImageSegmentaion2Models, - int imageWidth, - int imageHeight - ) - { - Ailia.AILIAShape shape = null; - // switch (ImageSegmentaion2Models) - // { - // case ImageSegmentaion2Models.HRNetV2_W18_Small_v2: - // case ImageSegmentaion2Models.HRNetV2_W18_Small_v1: - // case ImageSegmentaion2Models.HRNetV2_W48: - // case ImageSegmentaion2Models.pspnet_hair_segmentation: - // case ImageSegmentaion2Models.deeplabv3: - // shape = ailiaModel.GetInputShape(); - // InputWidth = (int)shape.x; - // InputHeight = (int)shape.y; - // InputChannel = (int)shape.z; - // shape = ailiaModel.GetOutputShape(); - // OutputWidth = (int)shape.x; - // OutputHeight = (int)shape.y; - // OutputChannel = (int)shape.z; - // break; - - // case ImageSegmentaion2Models.hair_segmentation: - // shape = new Ailia.AILIAShape(); - // shape.x = 3; - // shape.y = (uint)imageWidth; - // shape.z = (uint)imageHeight; - // shape.w = 1; - // shape.dim = 4; - // ailiaModel.SetInputShape(shape); - // InputWidth = imageWidth; - // InputHeight = imageHeight; - // InputChannel = 3; - // OutputWidth = imageWidth; - // OutputHeight = imageHeight; - // OutputChannel = 1; - // break; - - // case ImageSegmentaion2Models.u2net: - // shape = ailiaModel.GetInputShape(); - // InputWidth = (int)shape.x; - // InputHeight = (int)shape.y; - // InputChannel = (int)shape.z; - // shape = ailiaModel.GetOutputShape(); - // OutputWidth = (int)shape.x; - // OutputHeight = (int)shape.y; - // OutputChannel = (int)shape.z; - // break; - - // case ImageSegmentaion2Models.modnet: - // shape = new Ailia.AILIAShape(); - // shape.x = (uint)imageWidth / 32 * 32; - // shape.y = (uint)imageHeight / 32 * 32; - // shape.z = 3; - // shape.w = 1; - // shape.dim = 4; - // ailiaModel.SetInputShape(shape); - // InputWidth = imageWidth / 32 * 32; - // InputHeight = imageHeight / 32 * 32; - // InputChannel = 3; - // shape = ailiaModel.GetOutputShape(); - // OutputWidth = (int)shape.x; - // OutputHeight = (int)shape.y; - // OutputChannel = (int)shape.z; - // Debug.Log("" + OutputChannel + "/" + OutputWidth + "/" + OutputHeight); - // //OutputWidth = AiliaImageSource.Width/32*32; - // //OutputHeight = AiliaImageSource.Height/32*32; - // //OutputChannel = 1; - // break; - // } - } - - public void AllocateInputAndOutputTensor( - ImageSegmentaion2Models ImageSegmentaion2Models, - int imageWidth, - int imageHeight - ) - { - SetInputShape(ImageSegmentaion2Models, imageWidth, imageHeight); - input = new float[InputWidth * InputHeight * InputChannel]; - output = new float[OutputWidth * OutputHeight * OutputChannel]; - outputImage = new Color32[OutputWidth * OutputHeight]; - } - - public bool ProcessFrame( - ImageSegmentaion2Models ImageSegmentaion2Models, - Color32[] inputImage, - int inputImageWidth, - int inputImageHeight - ) - { - inputImage = ResizeImage( - inputImage, - inputImageWidth, - inputImageHeight, - InputWidth, - InputHeight - ); - InputDataProcessing(ImageSegmentaion2Models, inputImage, input); - return ailiaModel.Predict(output, input); - } - - public (Color32[], int, int) PostProcesss( - ImageSegmentaion2Models ImageSegmentaion2Models, - int inputImageWidth, - int inputImageHeight - ) - { - // if (ImageSegmentaion2Models == ImageSegmentaion2Models.hair_segmentation) - // LabelPaintHairSegmentation(output, outputImage, Color.red); - // else if (ImageSegmentaion2Models == ImageSegmentaion2Models.pspnet_hair_segmentation) - // LabelPaintPspnet(output, outputImage, Color.red); - // else if ( - // ImageSegmentaion2Models == ImageSegmentaion2Models.u2net - // || ImageSegmentaion2Models == ImageSegmentaion2Models.modnet - // ) - // LabelPaintU2netModnet(output, outputImage, Color.green); - // else - LabelPaint(output, outputImage, OutputChannel, colorPalette); - - Color32[] resizedOutputImage = ResizeImage( - outputImage, - OutputWidth, - OutputHeight, - inputImageWidth, - inputImageHeight - ); - - return (resizedOutputImage, inputImageWidth, inputImageHeight); - } - - Color32[] ResizeImage( - Color32[] inputImage, - int tex_width, - int tex_height, - int InputWidth, - int InputHeight - ) - { - Color32[] outputImage = new Color32[InputWidth * InputHeight]; - for (int y = 0; y < InputHeight; y++) - { - for (int x = 0; x < InputWidth; x++) - { - int x2 = x * tex_width / InputWidth; - int y2 = y * tex_height / InputHeight; - outputImage[y * InputWidth + x] = inputImage[y2 * tex_width + x2]; - } - } - return outputImage; - } - - void InputDataProcessing( - ImageSegmentaion2Models ImageSegmentaion2Models, - Color32[] inputImage, - float[] processedInputBuffer - ) - { - float weight = 1f / 255f; - float bias = 0; - bool rgbRepeats = false; - // switch (ImageSegmentaion2Models) - // { - // case ImageSegmentaion2Models.hair_segmentation: - // rgbRepeats = true; - // break; - // case ImageSegmentaion2Models.pspnet_hair_segmentation: - // InputDataProcessing_PSP(inputImage, processedInputBuffer); - // return; - // case ImageSegmentaion2Models.deeplabv3: - // weight = 1f / 127.5f; - // bias = -1; - // break; - // case ImageSegmentaion2Models.modnet: - // weight = 1f / 127.5f; - // bias = -1; - // break; - // default: - // break; - // } - - // flatten input data - if (rgbRepeats) - { - for (int i = 0; i < inputImage.Length; i++) - { - // rgbrgbrgb... - processedInputBuffer[i * 3 + 0] = (inputImage[i].r) * weight + bias; - processedInputBuffer[i * 3 + 1] = (inputImage[i].g) * weight + bias; - processedInputBuffer[i * 3 + 2] = (inputImage[i].b) * weight + bias; - } - } - else - { - for (int i = 0; i < inputImage.Length; i++) - { - // rrr...ggg...bbb... - processedInputBuffer[i + inputImage.Length * 0] = (inputImage[i].r) * weight + bias; - processedInputBuffer[i + inputImage.Length * 1] = (inputImage[i].g) * weight + bias; - processedInputBuffer[i + inputImage.Length * 2] = (inputImage[i].b) * weight + bias; - } - } - } - - void InputDataProcessing_PSP(Color32[] inputImage, float[] processedInputBuffer) - { - for (int i = 0; i < inputImage.Length; i++) - { - // rrr...ggg...bbb... - processedInputBuffer[i + inputImage.Length * 0] = - (inputImage[i].r * (1f / 255f) - 0.485f) * (1f / 0.229f); - processedInputBuffer[i + inputImage.Length * 1] = - (inputImage[i].g * (1f / 255f) - 0.456f) * (1f / 0.224f); - processedInputBuffer[i + inputImage.Length * 2] = - (inputImage[i].b * (1f / 255f) - 0.406f) * (1f / 0.225f); - } - } - - void LabelPaint(float[] labelData, Color32[] pixelBuffer, int channel, Color32[] palette) - { - Debug.Assert(palette.Length >= channel, "wrong palette size"); - Debug.Assert(labelData.Length == pixelBuffer.Length * channel, "wrong parameter"); - - for (int i = 0; i < pixelBuffer.Length; i++) - { - int maxIndex = 0; - float maxValue = labelData[i + 0 * (pixelBuffer.Length)]; - for (int c = 1; c < channel; c++) - { - if (maxValue < labelData[i + c * pixelBuffer.Length]) - { - maxValue = labelData[i + c * pixelBuffer.Length]; - maxIndex = c; - } - } - pixelBuffer[i] = palette[maxIndex]; - } - } - - void LabelPaintHairSegmentation(float[] labelData, Color32[] pixelBuffer, Color32 color) - { - Debug.Assert(labelData.Length == pixelBuffer.Length, "wrong parameter"); - - for (int i = 0; i < pixelBuffer.Length; i++) - { - pixelBuffer[i] = color; - pixelBuffer[i].a = (byte)(Mathf.Clamp01(labelData[i]) * 255); - } - } - - void LabelPaintPspnet(float[] labelData, Color32[] pixelBuffer, Color32 color) - { - Debug.Assert(labelData.Length == pixelBuffer.Length, "wrong parameter"); - - for (int i = 0; i < pixelBuffer.Length; i++) - { - pixelBuffer[i] = color; - - float k = Mathf.Exp(labelData[i]); - pixelBuffer[i].a = (byte)(k / (1.0f + k) * 255); - } - } - - void LabelPaintU2netModnet(float[] labelData, Color32[] pixelBuffer, Color32 color) - { - Debug.Assert(labelData.Length == pixelBuffer.Length, "wrong parameter"); - for (int i = 0; i < pixelBuffer.Length; i++) - { - pixelBuffer[i] = color; - pixelBuffer[i].a = (byte)(255 - Mathf.Clamp01(labelData[i]) * 255); - } - } - - public void Destroy() - { - ailiaModel?.Close(); - } - - public string EnvironmentName() - { - return ailiaModel.EnvironmentName(); - } -} diff --git a/Assets/AXIP/AILIA-MODELS/ImageSegmentation2/Segmentation2Model.cs.meta b/Assets/AXIP/AILIA-MODELS/ImageSegmentation2/Segmentation2Model.cs.meta deleted file mode 100644 index 448898a4..00000000 --- a/Assets/AXIP/AILIA-MODELS/ImageSegmentation2/Segmentation2Model.cs.meta +++ /dev/null @@ -1,11 +0,0 @@ -fileFormatVersion: 2 -guid: 792762c74ff014b5597497355b65b6cd -MonoImporter: - externalObjects: {} - serializedVersion: 2 - defaultReferences: [] - executionOrder: 0 - icon: {instanceID: 0} - userData: - assetBundleName: - assetBundleVariant: From bfaae812db202f27a8c6b8a9d7444a62f349e6c6 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?=E3=82=AD=E3=83=A7=E3=83=BB=E3=83=AA=E3=83=BC=E3=82=B7?= =?UTF-8?q?=E3=83=A5=E3=83=B3?= Date: Mon, 16 Jun 2025 16:23:15 +0900 Subject: [PATCH 05/16] Remove unused image function --- .../SegmentAnything2Model.cs | 188 +----------------- 1 file changed, 6 insertions(+), 182 deletions(-) diff --git a/Assets/AXIP/AILIA-MODELS/ImageSegmentation2/SegmentAnything2Model.cs b/Assets/AXIP/AILIA-MODELS/ImageSegmentation2/SegmentAnything2Model.cs index 79e08162..cd37c44f 100644 --- a/Assets/AXIP/AILIA-MODELS/ImageSegmentation2/SegmentAnything2Model.cs +++ b/Assets/AXIP/AILIA-MODELS/ImageSegmentation2/SegmentAnything2Model.cs @@ -71,7 +71,7 @@ public void SetBoxCoords(Rect box) { boxCoords = box; - Debug.Log($"boxCoords set to {box.xMin},{box.yMin} {box.xMax},{box.yMax}"); + // Debug.Log($"boxCoords set to {box.xMin},{box.yMin} {box.xMax},{box.yMax}"); } public void AddClickPoint(int x, int y, bool negativePoint = false) @@ -636,38 +636,6 @@ private void RunEmbedding(Color32[] image, int imgWidth, int imgHeight) return result; } - private float[,] ResizeBilinear(float[,] input, int newH, int newW) - { - int srcH = input.GetLength(0); - int srcW = input.GetLength(1); - float[,] result = new float[newH, newW]; - - float scaleY = (float)srcH / newH; - float scaleX = (float)srcW / newW; - - for (int y = 0; y < newH; y++) - { - float srcY = y * scaleY; - int y0 = (int)Math.Floor(srcY); - int y1 = Math.Min(y0 + 1, srcH - 1); - float wy = srcY - y0; - - for (int x = 0; x < newW; x++) - { - float srcX = x * scaleX; - int x0 = (int)Math.Floor(srcX); - int x1 = Math.Min(x0 + 1, srcW - 1); - float wx = srcX - x0; - - float top = (1 - wx) * input[y0, x0] + wx * input[y0, x1]; - float bottom = (1 - wx) * input[y1, x0] + wx * input[y1, x1]; - result[y, x] = (1 - wy) * top + wy * bottom; - } - } - - return result; - } - private float[][,,] PrepareBackboneFeatures(BackboneOutputs backboneData) { int numFeatureLevels = 3; @@ -898,13 +866,6 @@ private float[] Flatten4D(float[,,,] input) return output; } - private struct InputData - { - public Vector2[] inputPoints; - public int[] inputLabels; - public Vector4? inputBox; // x1, y1, x2, y2 or similar - } - private struct BackboneOutputs { public float[,,,] visionFeatures; @@ -912,78 +873,6 @@ private struct BackboneOutputs public float[][,,,] backboneFpn; } - private InputData GetInputPoint( - List posPoints, - List negPoints, - Vector4? box = null - ) - { - // Handle nulls like Python version - if (posPoints == null) - { - if (negPoints == null && box == null) - { - posPoints = new List { new Vector2(0, 0) }; // <-- replace with actual default POINT1 - } - else - { - posPoints = new List(); - } - } - - if (negPoints == null) - { - negPoints = new List(); - } - - List inputPoints = new List(); - List inputLabels = new List(); - - foreach (var pt in posPoints) - { - inputPoints.Add(pt); - inputLabels.Add(1); - } - - foreach (var pt in negPoints) - { - inputPoints.Add(pt); - inputLabels.Add(0); - } - - return new InputData - { - inputPoints = inputPoints.ToArray(), - inputLabels = inputLabels.ToArray(), - inputBox = box - }; - } - - List ConvertFloatArrayToVector2List(float[,] points) - { - int rows = points.GetLength(0); - int cols = points.GetLength(1); - - if (cols != 2) - throw new System.ArgumentException("Input must have shape [N, 2]"); - - List result = new List(); - for (int i = 0; i < rows; i++) - { - float x = points[i, 0]; - float y = points[i, 1]; - result.Add(new Vector2(x, y)); - } - - return result; - } - - public struct ConcatPoints - { - public Vector2[] coords; - public int[] labels; - } - // Run Inference private (bool[][,], float[]) RunInference( int imgWidth, @@ -1005,67 +894,6 @@ float[] pointLabels try { - // Call the method - List posPoints = ConvertFloatArrayToVector2List(pointCoords); - InputData inputData = GetInputPoint(posPoints, null, null); - - // // Unpack the result - Vector2[] point_coords = inputData.inputPoints; - int[] point_labels = inputData.inputLabels; - Vector4? input_box = inputData.inputBox; - - ConcatPoints? concatPoints = null; - - if (point_coords != null && point_coords.Length > 0) - { - concatPoints = new ConcatPoints { coords = point_coords, labels = point_labels }; - } - - if (input_box.HasValue) - { - // Convert Vector4 box → 2 corner points - Vector4 box = input_box.Value; - Vector2 topLeft = new Vector2(box.x, box.y); - Vector2 bottomRight = new Vector2(box.z, box.w); - - Vector2[] boxCoords = new Vector2[] { topLeft, bottomRight }; - int[] boxLabels = new int[] { 2, 3 }; - - if (point_coords != null && point_coords.Length > 0) - { - // Merge box points + labels with user points - Vector2[] concatCoords = new Vector2[boxCoords.Length + point_coords.Length]; - int[] concatLabels = new int[boxLabels.Length + point_labels.Length]; - - boxCoords.CopyTo(concatCoords, 0); - point_coords.CopyTo(concatCoords, boxCoords.Length); - - boxLabels.CopyTo(concatLabels, 0); - point_labels.CopyTo(concatLabels, boxLabels.Length); - - concatPoints = new ConcatPoints - { - coords = concatCoords, - labels = concatLabels - }; - } - else - { - // Only box points - concatPoints = new ConcatPoints { coords = boxCoords, labels = boxLabels }; - } - } - else if (point_coords != null && point_coords.Length > 0) - { - // Only point prompts - concatPoints = new ConcatPoints { coords = point_coords, labels = point_labels }; - } - - if (concatPoints == null) - { - throw new System.Exception("concatPoints must exist"); - } - float[,] scaledCoords = ApplyCoordinateScaling(pointCoords, imgHeight, imgWidth); // Prepare point coordinates and labels @@ -1077,6 +905,11 @@ float[] pointLabels flattenedCoords[i * 2 + 1] = scaledCoords[i, 1]; } + for (int i = 0; i < flattenedCoords.Length; i++) + { + Debug.Log(flattenedCoords[i]); + } + // float[,,] maskInputDummy; float[] maskInputDummy; float[] masksEnable; @@ -1157,11 +990,6 @@ float[] pointLabels return (new bool[0][,], new float[0]); } - for (int i = 0; i < flattenedCoords.Length; i++) - { - Debug.Log(flattenedCoords[i]); - } - bool setCoordsResult = prompt.SetInputBlobData( flattenedCoords, (uint)promptCoordsIndex @@ -1536,10 +1364,6 @@ float[] pointLabels int maskArea = maskWidth * maskHeight; bool[][,] masksResult = new bool[numMasks][,]; - Debug.Log(maskWidth); - Debug.Log(maskHeight); - Debug.Log(maskArea); - for (int i = 0; i < numMasks; i++) { float[,,,] maskTensor = ReshapeToTensor( From 654473e11b784e40ad46fdf5d9f1e4832f95390f Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?=E3=82=AD=E3=83=A7=E3=83=BB=E3=83=AA=E3=83=BC=E3=82=B7?= =?UTF-8?q?=E3=83=A5=E3=83=B3?= Date: Mon, 16 Jun 2025 17:04:52 +0900 Subject: [PATCH 06/16] Remove comments --- .../SegmentAnything2Model.cs | 55 +++++++------------ 1 file changed, 20 insertions(+), 35 deletions(-) diff --git a/Assets/AXIP/AILIA-MODELS/ImageSegmentation2/SegmentAnything2Model.cs b/Assets/AXIP/AILIA-MODELS/ImageSegmentation2/SegmentAnything2Model.cs index cd37c44f..665ca3a5 100644 --- a/Assets/AXIP/AILIA-MODELS/ImageSegmentation2/SegmentAnything2Model.cs +++ b/Assets/AXIP/AILIA-MODELS/ImageSegmentation2/SegmentAnything2Model.cs @@ -292,7 +292,6 @@ private float[] GetPointLabels() } // Run Embedding - private void RunEmbedding(Color32[] image, int imgWidth, int imgHeight) { if (isQuitting || !modelsInitialized || encoder == null || decoder == null) @@ -310,10 +309,10 @@ private void RunEmbedding(Color32[] image, int imgWidth, int imgHeight) // Set encoder input shape (1x3x1024x1024) ailia.Ailia.AILIAShape encInputShape = new ailia.Ailia.AILIAShape(); encInputShape.dim = 4; - encInputShape.w = 1; // batch=1 - encInputShape.z = 3; // channels=3 (RGB) - encInputShape.y = (uint)targetSize; // height=1024 - encInputShape.x = (uint)targetSize; // width=1024 + encInputShape.w = 1; + encInputShape.z = 3; + encInputShape.y = (uint)targetSize; + encInputShape.x = (uint)targetSize; if (isQuitting || encoder == null) { @@ -330,7 +329,6 @@ private void RunEmbedding(Color32[] image, int imgWidth, int imgHeight) bool dataSetResult = encoder.SetInputBlobData(nchw, imgIndex); // Debug.Log($"updated SET DATA {dataSetResult}"); - // Run encoder bool encResult = encoder.Update(); if (isQuitting || encoder == null) @@ -371,7 +369,6 @@ private void RunEmbedding(Color32[] image, int imgWidth, int imgHeight) return; } - // Get blob shapes ailia.Ailia.AILIAShape visionFeaturesBlobShape = encoder.GetBlobShape( (uint)visionFeaturesBlobIndex ); @@ -545,7 +542,7 @@ private void RunEmbedding(Color32[] image, int imgWidth, int imgHeight) (int H, int W) = bbFeatSizes[revIndex]; // H, W int HW = feat.GetLength(0); - int one = feat.GetLength(1); // should be 1 + int one = feat.GetLength(1); int C = feat.GetLength(2); if (HW != H * W) @@ -613,7 +610,6 @@ private void RunEmbedding(Color32[] image, int imgWidth, int imgHeight) int b1 = b.GetLength(1); int b2 = b.GetLength(2); - // Check dimension compatibility (broadcasting rules) if ((b0 != 1 && b0 != a0) || (b1 != 1 && b1 != a1) || (b2 != 1 && b2 != a2)) throw new ArgumentException("Incompatible shapes for broadcasting."); @@ -729,10 +725,9 @@ private void RunEmbedding(Color32[] image, int imgWidth, int imgHeight) // Generates one sample from a Gaussian distribution using Box-Muller transform private float NextGaussian(float mean = 0, float stdDev = 1) { - // Use Box-Muller transform to generate a normal distributed value - double u1 = 1.0 - _rng.NextDouble(); // uniform(0,1] random doubles + double u1 = 1.0 - _rng.NextDouble(); double u2 = 1.0 - _rng.NextDouble(); - double randStdNormal = Math.Sqrt(-2.0 * Math.Log(u1)) * Math.Sin(2.0 * Math.PI * u2); // random normal(0,1) + double randStdNormal = Math.Sqrt(-2.0 * Math.Log(u1)) * Math.Sin(2.0 * Math.PI * u2); return (float)(mean + stdDev * randStdNormal); } @@ -926,7 +921,6 @@ float[] pointLabels // masksEnable = new int[] { 1 }; // } - // Get blob indices int promptCoordsIndex = prompt.FindBlobIndexByName("coords"); int promptLabelsIndex = prompt.FindBlobIndexByName("labels"); int promptMasksIndex = prompt.FindBlobIndexByName("masks"); @@ -942,20 +936,17 @@ float[] pointLabels return (new bool[0][,], new float[0]); } - // point_coords: 1x1x2 ailia.Ailia.AILIAShape concatPointShape = new ailia.Ailia.AILIAShape(); concatPointShape.dim = 3; - concatPointShape.z = 1; // batch=1 - concatPointShape.y = 1; // points count (1) - concatPointShape.x = 2; // 2D coords (x,y) + concatPointShape.z = 1; + concatPointShape.y = 1; + concatPointShape.x = 2; - // // point_labels: 1x1 ailia.Ailia.AILIAShape labelsShape = new ailia.Ailia.AILIAShape(); labelsShape.dim = 2; - labelsShape.y = 1; // batch=1 + labelsShape.y = 1; labelsShape.x = 1; // points count (1) - // maskunput dummy ailia.Ailia.AILIAShape masksShape = new ailia.Ailia.AILIAShape(); masksShape.dim = 3; masksShape.z = 1; @@ -1010,7 +1001,6 @@ float[] pointLabels return (new bool[0][,], new float[0]); } - // Run prompt bool promptResult = prompt.Update(); if (isQuitting || prompt == null) @@ -1046,7 +1036,6 @@ float[] pointLabels return (new bool[0][,], new float[0]); } - // Get blob shapes ailia.Ailia.AILIAShape sparseEmbeddingsBlobShape = prompt.GetBlobShape( (uint)sparseEmbeddingsBlobIndex ); @@ -1078,7 +1067,6 @@ float[] pointLabels prompt.GetBlobData(denseEmbeddingsOutput, denseEmbeddingsBlobIndex); prompt.GetBlobData(densePeOutput, densePeBlobIndex); - // Identify mask and score blobs int imageEmbeddingsIndex = decoder.FindBlobIndexByName("image_embeddings"); int imagePeIndex = decoder.FindBlobIndexByName("image_pe"); int sparsePromptEmbeddingsIndex = decoder.FindBlobIndexByName( @@ -1144,8 +1132,8 @@ float[] pointLabels highResFeatures2Shape.dim = 4; highResFeatures2Shape.w = 1; // batch=1 highResFeatures2Shape.z = 64; // channel=256 - highResFeatures2Shape.y = 128; // height=64 - highResFeatures2Shape.x = 128; // width=64 + highResFeatures2Shape.y = 128; // height=128 + highResFeatures2Shape.x = 128; // width=128 bool imageEmbeddingsShapeResult = decoder.SetInputBlobShape( imageEmbeddingsShape, @@ -1237,7 +1225,6 @@ float[] pointLabels return (new bool[0][,], new float[0]); } - // Run decoder bool decoderResult = decoder.Update(); if (isQuitting || decoder == null) @@ -1258,7 +1245,6 @@ float[] pointLabels } // masks, iou_pred, sam_tokens_out, object_score_logits = mask_decoder.run - // Get blob shapes int masksBlobIndex = decoder.FindBlobIndexByName("masks"); int iouPredBlobIndex = decoder.FindBlobIndexByName("iou_pred"); int samTokensOutBlobIndex = decoder.FindBlobIndexByName("sam_tokens_out"); @@ -1566,7 +1552,7 @@ private float GetScale(int texWidth, int texHeight) int imageSize ) { - // 2. Resize image to (imageSize, imageSize) + // Resize image to (imageSize, imageSize) float scale = GetScale(originalWidth, originalHeight); int newWidth = imageSize; int newHeight = imageSize; @@ -1578,10 +1564,10 @@ int imageSize newHeight ); - // 3. Convert Color32[] to float[height, width, channels] normalized 0-1 + // Convert Color32[] to float[height, width, channels] float[,,] floatImage = Color32ArrayToFloatArray(resizedImage, newHeight, newWidth); - // 4. Normalize per channel (subtract mean, divide std) + // Normalize per channel (subtract mean, divide std) float[] mean = new float[] { 0.485f, 0.456f, 0.406f }; float[] std = new float[] { 0.229f, 0.224f, 0.225f }; @@ -1596,10 +1582,10 @@ int imageSize } } - // 5. Transpose (H, W, C) => (C, H, W) + // Transpose (H, W, C) => (C, H, W) float[,,] chw = TransposeHWCtoCHW(floatImage); - // 6. Add batch dimension => (1, C, H, W) + // Add batch dimension => (1, C, H, W) float[,,,] batch = new float[1, 3, newHeight, newWidth]; for (int c = 0; c < 3; c++) for (int h = 0; h < newHeight; h++) @@ -1609,7 +1595,7 @@ int imageSize return batch; } - // Helper: Resize Color32[] with nearest neighbor (or implement your own) + // Helper: Resize Color32[] with nearest neighbor private Color32[] ResizeColor32( Color32[] src, int srcWidth, @@ -1631,7 +1617,6 @@ int dstHeight return dst; } - // Helper: Convert Color32[] to float[height,width,channels], normalized to [0..1] private float[,,] Color32ArrayToFloatArray(Color32[] image, int height, int width) { float[,,] result = new float[height, width, 3]; @@ -1647,7 +1632,7 @@ int dstHeight return result; } - // Helper: Transpose (H,W,C) => (C,H,W) + // Transpose (H,W,C) => (C,H,W) private float[,,] TransposeHWCtoCHW(float[,,] input) { int H = input.GetLength(0); From 869962c587929a3c035a96d38e96fdc544e84b54 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?=E3=82=AD=E3=83=A7=E3=83=BB=E3=83=AA=E3=83=BC=E3=82=B7?= =?UTF-8?q?=E3=83=A5=E3=83=B3?= Date: Tue, 17 Jun 2025 15:43:33 +0900 Subject: [PATCH 07/16] Move SAM2 to one folder --- .../AiliaImageSegmentationSample.cs | 166 ++++-- .../SegmentAnything2Model.cs | 14 +- .../SegmentAnything2Model.cs.meta | 2 +- .../AiliaImageSegmentation2Sample.cs | 490 ---------------- .../AiliaImageSegmentation2Sample.cs.meta | 11 - .../ImageSegmentation2Sample.unity | 548 ------------------ .../ImageSegmentation2Sample.unity.meta | 7 - .../ImageSegmentation2/SampleImage.meta | 8 - .../ImageSegmentation2/SampleImage/couple.jpg | Bin 20290 -> 0 bytes .../SampleImage/couple.jpg.meta | 152 ----- .../ImageSegmentation2/SampleImage/girl.png | Bin 234498 -> 0 bytes .../SampleImage/girl.png.meta | 152 ----- .../ImageSegmentation2/SampleImage/hair.jpg | Bin 25632 -> 0 bytes .../SampleImage/hair.jpg.meta | 152 ----- .../ImageSegmentation2/SampleImage/hair2.jpg | Bin 54460 -> 0 bytes .../SampleImage/hair2.jpg.meta | 152 ----- .../ImageSegmentation2/SampleImage/modnet.jpg | Bin 48615 -> 0 bytes .../SampleImage/modnet.jpg.meta | 152 ----- .../ImageSegmentation2/SampleImage/road.png | Bin 92863 -> 0 bytes .../SampleImage/road.png.meta | 152 ----- .../ImageSegmentation2/SampleImage/truck.jpg | Bin 271475 -> 0 bytes .../SampleImage/truck.jpg.meta | 159 ----- 22 files changed, 121 insertions(+), 2196 deletions(-) rename Assets/AXIP/AILIA-MODELS/{ImageSegmentation2 => ImageSegmentation}/SegmentAnything2Model.cs (99%) rename Assets/AXIP/AILIA-MODELS/{ImageSegmentation2 => ImageSegmentation}/SegmentAnything2Model.cs.meta (83%) delete mode 100644 Assets/AXIP/AILIA-MODELS/ImageSegmentation2/AiliaImageSegmentation2Sample.cs delete mode 100644 Assets/AXIP/AILIA-MODELS/ImageSegmentation2/AiliaImageSegmentation2Sample.cs.meta delete mode 100644 Assets/AXIP/AILIA-MODELS/ImageSegmentation2/ImageSegmentation2Sample.unity delete mode 100644 Assets/AXIP/AILIA-MODELS/ImageSegmentation2/ImageSegmentation2Sample.unity.meta delete mode 100644 Assets/AXIP/AILIA-MODELS/ImageSegmentation2/SampleImage.meta delete mode 100644 Assets/AXIP/AILIA-MODELS/ImageSegmentation2/SampleImage/couple.jpg delete mode 100644 Assets/AXIP/AILIA-MODELS/ImageSegmentation2/SampleImage/couple.jpg.meta delete mode 100644 Assets/AXIP/AILIA-MODELS/ImageSegmentation2/SampleImage/girl.png delete mode 100644 Assets/AXIP/AILIA-MODELS/ImageSegmentation2/SampleImage/girl.png.meta delete mode 100644 Assets/AXIP/AILIA-MODELS/ImageSegmentation2/SampleImage/hair.jpg delete mode 100644 Assets/AXIP/AILIA-MODELS/ImageSegmentation2/SampleImage/hair.jpg.meta delete mode 100644 Assets/AXIP/AILIA-MODELS/ImageSegmentation2/SampleImage/hair2.jpg delete mode 100644 Assets/AXIP/AILIA-MODELS/ImageSegmentation2/SampleImage/hair2.jpg.meta delete mode 100644 Assets/AXIP/AILIA-MODELS/ImageSegmentation2/SampleImage/modnet.jpg delete mode 100644 Assets/AXIP/AILIA-MODELS/ImageSegmentation2/SampleImage/modnet.jpg.meta delete mode 100644 Assets/AXIP/AILIA-MODELS/ImageSegmentation2/SampleImage/road.png delete mode 100644 Assets/AXIP/AILIA-MODELS/ImageSegmentation2/SampleImage/road.png.meta delete mode 100644 Assets/AXIP/AILIA-MODELS/ImageSegmentation2/SampleImage/truck.jpg delete mode 100644 Assets/AXIP/AILIA-MODELS/ImageSegmentation2/SampleImage/truck.jpg.meta diff --git a/Assets/AXIP/AILIA-MODELS/ImageSegmentation/AiliaImageSegmentationSample.cs b/Assets/AXIP/AILIA-MODELS/ImageSegmentation/AiliaImageSegmentationSample.cs index ff202629..a15d7451 100644 --- a/Assets/AXIP/AILIA-MODELS/ImageSegmentation/AiliaImageSegmentationSample.cs +++ b/Assets/AXIP/AILIA-MODELS/ImageSegmentation/AiliaImageSegmentationSample.cs @@ -21,7 +21,8 @@ public enum ImageSegmentaionModels deeplabv3, u2net, modnet, - segment_anything1 + segment_anything1, + segment_anything2 } public class AiliaImageSegmentationSample : MonoBehaviour @@ -69,6 +70,7 @@ public class AiliaImageSegmentationSample : MonoBehaviour // Segment Anything Model private SegmentationModel segModel; private SegmentAnythingModel samModel; + private SegmentAnything2Model sam2Model; private bool isDraggingForBox = false; private Rect boxRect = new (); @@ -122,13 +124,18 @@ void UISetup() raw_image = UICanvas.transform.Find("RawImage").GetComponent(); raw_image.gameObject.SetActive(false); - if (imageSegmentaionModels == ImageSegmentaionModels.segment_anything1) { - mode_text.text = "ailia Image Segmentation\n" + + switch (imageSegmentaionModels) + { + case ImageSegmentaionModels.segment_anything1: + case ImageSegmentaionModels.segment_anything2: + mode_text.text = "ailia Image Segmentation\n" + "Left/Right click: positive/negative point\n" + "Middle click: drag to define border box\n" + "Space key down to reset"; - } else { - mode_text.text = "ailia Image Segmentation"; + break; + default: + mode_text.text = "ailia Image Segmentation"; + break; } } Color32 [] VerticalFlip(Color32[] inputImage, int InputWidth, int InputHeight){ @@ -151,8 +158,14 @@ void Update() } if (modelPrepared && !modelAllocated) { - if (imageSegmentaionModels != ImageSegmentaionModels.segment_anything1){ - segModel.AllocateInputAndOutputTensor(imageSegmentaionModels, AiliaImageSource.Width, AiliaImageSource.Height); + switch (imageSegmentaionModels) + { + case ImageSegmentaionModels.segment_anything1: + case ImageSegmentaionModels.segment_anything2: + break; + default: + segModel.AllocateInputAndOutputTensor(imageSegmentaionModels, AiliaImageSource.Width, AiliaImageSource.Height); + break; } modelAllocated = true; } @@ -164,10 +177,20 @@ void Update() // When space key down, draw original image if (Input.GetKey(KeyCode.Space)) { - if (imageSegmentaionModels == ImageSegmentaionModels.segment_anything1){ - samModel.ResetClickPoint(); - boxRect = new(); - oneshot = true; + switch (imageSegmentaionModels) + { + case ImageSegmentaionModels.segment_anything1: + samModel.ResetClickPoint(); + boxRect = new(); + oneshot = true; + break; + case ImageSegmentaionModels.segment_anything2: + sam2Model.ResetClickPoint(); + boxRect = new(); + oneshot = true; + break; + default: + break; } blendMaterial.SetFloat(blendFlagId, 0); } @@ -206,25 +229,38 @@ void Update() long start_time2 = DateTime.UtcNow.Ticks / TimeSpan.TicksPerMillisecond; bool result = false; - if (imageSegmentaionModels == ImageSegmentaionModels.segment_anything1) + switch (imageSegmentaionModels) { - if (!samModel.EmbeddingExist()){ - if (samModel.GetClickPoints(0).Length == 0) - { - samModel.AddClickPoint(inputImageWidth / 4, inputImageHeight / 4 + 30); + case ImageSegmentaionModels.segment_anything1: + if (!samModel.EmbeddingExist()){ + if (samModel.GetClickPoints(0).Length == 0) + { + samModel.AddClickPoint(inputImageWidth / 4, inputImageHeight / 4 + 30); + } } - } - if (camera_mode || !samModel.EmbeddingExist()){ - samModel.ProcessEmbedding(inputImage, inputImageWidth, inputImageHeight); - } - samModel.ProcessMask(inputImage, inputImageWidth, inputImageHeight); - result = samModel.success; - } - else - { - result = segModel.ProcessFrame(imageSegmentaionModels, inputImage, inputImageWidth, inputImageHeight); - } - + if (camera_mode || !samModel.EmbeddingExist()){ + samModel.ProcessEmbedding(inputImage, inputImageWidth, inputImageHeight); + } + samModel.ProcessMask(inputImage, inputImageWidth, inputImageHeight); + result = samModel.success; + break; + case ImageSegmentaionModels.segment_anything2: + if (!sam2Model.EmbeddingExist()){ + if (sam2Model.GetClickPoints(0).Length == 0) + { + sam2Model.AddClickPoint(inputImageWidth / 4, inputImageHeight / 4 + 30); + } + } + if (camera_mode || !sam2Model.EmbeddingExist()){ + sam2Model.ProcessEmbedding(inputImage, inputImageWidth, inputImageHeight); + } + sam2Model.ProcessMask(inputImage, inputImageWidth, inputImageHeight); + result = sam2Model.success; + break; + default: + result = segModel.ProcessFrame(imageSegmentaionModels, inputImage, inputImageWidth, inputImageHeight); + break; + } if (!result) { @@ -235,14 +271,22 @@ void Update() // convert result to image Color32[] outputImage; int outputWidth, outputHeight; - if (imageSegmentaionModels == ImageSegmentaionModels.segment_anything1) + switch (imageSegmentaionModels) { - outputImage = samModel.visualizedResult.GetPixels32(); - outputWidth = samModel.visualizedResult.width; - outputHeight = samModel.visualizedResult.height; - } - else{ - (outputImage, outputWidth, outputHeight) = segModel.PostProcesss(imageSegmentaionModels, inputImageWidth, inputImageHeight); + case ImageSegmentaionModels.segment_anything1: + outputImage = samModel.visualizedResult.GetPixels32(); + outputWidth = samModel.visualizedResult.width; + outputHeight = samModel.visualizedResult.height; + break; + case ImageSegmentaionModels.segment_anything2: + outputImage = sam2Model.visualizedResult.GetPixels32(); + outputWidth = sam2Model.visualizedResult.width; + outputHeight = sam2Model.visualizedResult.height; + break; + default: + (outputImage, outputWidth, outputHeight) = segModel.PostProcesss(imageSegmentaionModels, inputImageWidth, inputImageHeight); + break; + } long end_time2 = DateTime.UtcNow.Ticks / TimeSpan.TicksPerMillisecond; @@ -288,29 +332,39 @@ void CreateAiliaNet(ImageSegmentaionModels modelType, bool gpu_mode = true) ailia_download.DownloaderProgressPanel = UICanvas.transform.Find("DownloaderProgressPanel").gameObject; List urlList = null; - if (imageSegmentaionModels == ImageSegmentaionModels.segment_anything1) + switch (imageSegmentaionModels) { - samModel = new SegmentAnythingModel(); - urlList = samModel.GetModelURLs(imageSegmentaionModels); + case ImageSegmentaionModels.segment_anything1: + samModel = new SegmentAnythingModel(); + urlList = samModel.GetModelURLs(imageSegmentaionModels); + break; + case ImageSegmentaionModels.segment_anything2: + sam2Model = new SegmentAnything2Model(); + urlList = sam2Model.GetModelURLs(imageSegmentaionModels); + break; + default: + segModel = new SegmentationModel(); + urlList = segModel.GetModelURLs(imageSegmentaionModels); + break; } - else - { - segModel = new SegmentationModel(); - urlList = segModel.GetModelURLs(imageSegmentaionModels); - } StartCoroutine(ailia_download.DownloadWithProgressFromURL(urlList, () => { - if (imageSegmentaionModels == ImageSegmentaionModels.segment_anything1) - { - modelPrepared = samModel.InitializeModels(imageSegmentaionModels, gpu_mode); - envName = samModel.EnvironmentName(); - } - else - { - modelPrepared = segModel.InitializeModels(imageSegmentaionModels, gpu_mode); - envName = segModel.EnvironmentName(); - } + switch (imageSegmentaionModels) + { + case ImageSegmentaionModels.segment_anything1: + modelPrepared = samModel.InitializeModels(imageSegmentaionModels, gpu_mode); + envName = samModel.EnvironmentName(); + break; + case ImageSegmentaionModels.segment_anything2: + modelPrepared = sam2Model.InitializeModels(imageSegmentaionModels, gpu_mode); + envName = sam2Model.EnvironmentName(); + break; + default: + modelPrepared = segModel.InitializeModels(imageSegmentaionModels, gpu_mode); + envName = segModel.EnvironmentName(); + break; + } })); } @@ -340,6 +394,7 @@ void LoadImage(ImageSegmentaionModels imageSegmentaionModels, AiliaImageSource a ailiaImageSource.CreateSource(image_source_modnet); break; case ImageSegmentaionModels.segment_anything1: + case ImageSegmentaionModels.segment_anything2: ailiaImageSource.CreateSource(image_source_sam1); break; } @@ -376,6 +431,7 @@ void HandleClick(bool leftClick, bool rightClick, bool middleClick) if (leftClick || rightClick) { samModel?.AddClickPoint(x, y, rightClick); + sam2Model?.AddClickPoint(x, y, rightClick); oneshot = true; Debug.Log($"Click registered at: {x}, {y}"); @@ -402,6 +458,7 @@ void HandleClick(bool leftClick, bool rightClick, bool middleClick) boxRect.yMax = Math.Max(firstY, y); samModel.SetBoxCoords(boxRect); + sam2Model.SetBoxCoords(boxRect); oneshot = true; } } @@ -470,6 +527,9 @@ void DestroyAiliaDetector() if (samModel != null){ samModel.Destroy(); } + if (sam2Model != null){ + sam2Model.Destroy(); + } if (segModel != null){ segModel.Destroy(); } diff --git a/Assets/AXIP/AILIA-MODELS/ImageSegmentation2/SegmentAnything2Model.cs b/Assets/AXIP/AILIA-MODELS/ImageSegmentation/SegmentAnything2Model.cs similarity index 99% rename from Assets/AXIP/AILIA-MODELS/ImageSegmentation2/SegmentAnything2Model.cs rename to Assets/AXIP/AILIA-MODELS/ImageSegmentation/SegmentAnything2Model.cs index 665ca3a5..2ce60796 100644 --- a/Assets/AXIP/AILIA-MODELS/ImageSegmentation2/SegmentAnything2Model.cs +++ b/Assets/AXIP/AILIA-MODELS/ImageSegmentation/SegmentAnything2Model.cs @@ -21,14 +21,13 @@ public class SegmentAnything2Model private const string encoderProtoPath = "image_encoder_hiera_l.onnx.prototxt"; private const string decoderWeightPath = "mask_decoder_hiera_l.onnx"; private const string decoderProtoPath = "mask_decoder_hiera_l.onnx.prototxt"; + private const string promptWeightPath = "prompt_encoder_hiera_l.onnx"; + private const string promptProtoPath = "prompt_encoder_hiera_l.onnx.prototxt"; // private const string memAttentionWeightPath = "memory_attention_hiera_l.opt.onnx"; // private const string memAttentionProtoPath = "memory_attention_hiera_l.opt.onnx.prototxt"; // private const string encoderMemWeightPath = "memory_encoder_hiera_l.onnx"; // private const string encoderMemProtoPath = "memory_encoder_hiera_l.onnx.prototxt"; - private const string promptWeightPath = "prompt_encoder_hiera_l.onnx"; - private const string promptProtoPath = "prompt_encoder_hiera_l.onnx.prototxt"; - // private const string mlpWeightPath = "mlp_hiera_l.onnx"; // private const string mlpProtoPath = "mlp_hiera_l.onnx.prototxt"; @@ -87,7 +86,7 @@ public void ResetClickPoint() boxCoords = new(); } - public List GetModelURLs(ImageSegmentaion2Models modelType) + public List GetModelURLs(ImageSegmentaionModels modelType) { List modelDownloadURLs = new List(); string serverFolderName = "segment-anything-2"; @@ -133,7 +132,7 @@ public List GetModelURLs(ImageSegmentaion2Models modelType) } // Initialize Ailia models - public bool InitializeModels(ImageSegmentaion2Models modelType, bool gpuMode) + public bool InitializeModels(ImageSegmentaionModels modelType, bool gpuMode) { if (modelsInitialized) return true; @@ -939,13 +938,13 @@ float[] pointLabels ailia.Ailia.AILIAShape concatPointShape = new ailia.Ailia.AILIAShape(); concatPointShape.dim = 3; concatPointShape.z = 1; - concatPointShape.y = 1; + concatPointShape.y = (uint)pointCount; concatPointShape.x = 2; ailia.Ailia.AILIAShape labelsShape = new ailia.Ailia.AILIAShape(); labelsShape.dim = 2; labelsShape.y = 1; - labelsShape.x = 1; // points count (1) + labelsShape.x = (uint)pointCount; // points count (1) ailia.Ailia.AILIAShape masksShape = new ailia.Ailia.AILIAShape(); masksShape.dim = 3; @@ -1856,6 +1855,7 @@ public void Destroy() { encoder.Close(); decoder.Close(); + prompt.Close(); } public string EnvironmentName() diff --git a/Assets/AXIP/AILIA-MODELS/ImageSegmentation2/SegmentAnything2Model.cs.meta b/Assets/AXIP/AILIA-MODELS/ImageSegmentation/SegmentAnything2Model.cs.meta similarity index 83% rename from Assets/AXIP/AILIA-MODELS/ImageSegmentation2/SegmentAnything2Model.cs.meta rename to Assets/AXIP/AILIA-MODELS/ImageSegmentation/SegmentAnything2Model.cs.meta index f9048523..883e85a6 100644 --- a/Assets/AXIP/AILIA-MODELS/ImageSegmentation2/SegmentAnything2Model.cs.meta +++ b/Assets/AXIP/AILIA-MODELS/ImageSegmentation/SegmentAnything2Model.cs.meta @@ -1,5 +1,5 @@ fileFormatVersion: 2 -guid: 3e2f283a42dd549d08dca69966687c1c +guid: 935784dca03c0456fadcddf73e6ec180 MonoImporter: externalObjects: {} serializedVersion: 2 diff --git a/Assets/AXIP/AILIA-MODELS/ImageSegmentation2/AiliaImageSegmentation2Sample.cs b/Assets/AXIP/AILIA-MODELS/ImageSegmentation2/AiliaImageSegmentation2Sample.cs deleted file mode 100644 index 2a086904..00000000 --- a/Assets/AXIP/AILIA-MODELS/ImageSegmentation2/AiliaImageSegmentation2Sample.cs +++ /dev/null @@ -1,490 +0,0 @@ -/* AILIA Unity Plugin Segmentation Sample */ -/* Copyright 2018-2022 AXELL CORPORATION */ - -using System; -using System.Collections.Generic; -using UnityEngine; -using UnityEngine.UI; - -using ailia; - -namespace ailiaSDK -{ - // Model list - public enum ImageSegmentaion2Models - { - image_encoder_hiera_l - } - - public class AiliaImageSegmentation2Sample : MonoBehaviour - { - // Settings - public ImageSegmentaion2Models ImageSegmentaion2Models = - ImageSegmentaion2Models.image_encoder_hiera_l; - public bool gpu_mode = false; - public GameObject UICanvas = null; - public bool camera_mode = true; - public int camera_id = 0; - - // Result - RawImage raw_image = null; - Text label_text = null; - Text mode_text = null; - private bool oneshot = true; - - // AILIA - private AiliaCamera ailia_camera = new AiliaCamera(); - - // Input source - AiliaImageSource AiliaImageSource; - public Texture2D image_source_sam2 = null; - - // Pre-and-Post processing Shader - Material blendMaterial; - int mainTexId; - int blendTexId; - int blendFlagId; - int mainVFlipId; - int blendVFlipId; - - // Model input and output - - Texture2D labelTexture; - Texture2D originalTexture; - Vector2 rawImageSize; - - // Segment Anything Model - private SegmentAnything2Model sam2Model; - private bool isDraggingForBox = false; - private Rect boxRect = new(); - - bool modelPrepared = false; - bool modelAllocated = false; - string envName = ""; - - async void Start() - { - Debug.Log("Start"); - AiliaLicense.CheckAndDownloadLicense(); - UISetup(); - - AiliaImageSource = gameObject.GetComponent(); - - // for Rendering - blendMaterial = new Material(Shader.Find("Ailia/AlphaBlending2Tex")); - mainTexId = Shader.PropertyToID("_MainTex"); - blendTexId = Shader.PropertyToID("_BlendTex"); - blendFlagId = Shader.PropertyToID("blendFlag"); - mainVFlipId = Shader.PropertyToID("mainVFlip"); - blendVFlipId = Shader.PropertyToID("blendVFlip"); - raw_image.material = blendMaterial; - - rawImageSize = raw_image.rectTransform.sizeDelta; - - // for Processing - AiliaInit(); - - // for Camera - if (camera_mode) - { - bool crop_square = false; - ailia_camera.CreateCamera(camera_id, crop_square); - } - } - - void AiliaInit() - { - // Create Ailia - CreateAiliaNet(ImageSegmentaion2Models, gpu_mode); - - // Load sample image - LoadImage(ImageSegmentaion2Models, AiliaImageSource); - } - - void UISetup() - { - Debug.Assert(UICanvas != null, "UICanvas is null"); - - label_text = UICanvas.transform.Find("LabelText").GetComponent(); - mode_text = UICanvas.transform.Find("ModeLabel").GetComponent(); - raw_image = UICanvas.transform.Find("RawImage").GetComponent(); - raw_image.gameObject.SetActive(false); - - if (ImageSegmentaion2Models == ImageSegmentaion2Models.image_encoder_hiera_l) - { - mode_text.text = - "ailia Image Segmentation 2\n" - + "Left/Right click: positive/negative point\n" - + "Middle click: drag to define border box\n" - + "Space key down to reset"; - } - else - { - mode_text.text = "ailia Image Segmentation 2"; - } - } - - Color32[] VerticalFlip(Color32[] inputImage, int InputWidth, int InputHeight) - { - Color32[] outputImage = new Color32[InputWidth * InputHeight]; - for (int y = 0; y < InputHeight; y++) - { - for (int x = 0; x < InputWidth; x++) - { - outputImage[(InputHeight - 1 - y) * InputWidth + x] = inputImage[ - y * InputWidth + x - ]; - } - } - return outputImage; - } - - void Update() - { - HandleClick(Input.GetMouseButton(0), Input.GetMouseButton(1), Input.GetMouseButton(2)); - - if (AiliaImageSource == null || !AiliaImageSource.IsPrepared || !modelPrepared) - { - return; - } - if (modelPrepared && !modelAllocated) - { - modelAllocated = true; - } - if (camera_mode && !ailia_camera.IsEnable()) - { - return; - } - - // When space key down, draw original image - if (Input.GetKey(KeyCode.Space)) - { - if (ImageSegmentaion2Models == ImageSegmentaion2Models.image_encoder_hiera_l) - { - sam2Model.ResetClickPoint(); - boxRect = new(); - oneshot = true; - } - blendMaterial.SetFloat(blendFlagId, 0); - } - else - { - blendMaterial.SetFloat(blendFlagId, 1); - } - - // Only one shot processing for image mode - if (!oneshot && !camera_mode) - { - return; - } - - // Make input data - long start_time = DateTime.UtcNow.Ticks / TimeSpan.TicksPerMillisecond; - Color32[] inputImage = null; - int inputImageWidth = 0; - int inputImageHeight = 0; - if (camera_mode) - { - inputImageWidth = ailia_camera.GetWidth(); - inputImageHeight = ailia_camera.GetHeight(); - inputImage = ailia_camera.GetPixels32(); // Bottom2Top format - inputImage = VerticalFlip(inputImage, inputImageWidth, inputImageHeight); // Top2Bottom format - } - else - { - bool convert_to_top2bottom = true; - inputImageWidth = AiliaImageSource.Width; - inputImageHeight = AiliaImageSource.Height; - Rect rect = new Rect(0, 0, inputImageWidth, inputImageHeight); - inputImage = AiliaImageSource.GetPixels32(rect, convert_to_top2bottom); // Top2Bottom format - } - - long end_time = DateTime.UtcNow.Ticks / TimeSpan.TicksPerMillisecond; - - // Predict - long start_time2 = DateTime.UtcNow.Ticks / TimeSpan.TicksPerMillisecond; - - bool result = false; - if (ImageSegmentaion2Models == ImageSegmentaion2Models.image_encoder_hiera_l) - { - if (!sam2Model.EmbeddingExist()) - { - if (sam2Model.GetClickPoints(0).Length == 0) - { - sam2Model.AddClickPoint(inputImageWidth / 4, inputImageHeight / 4 + 30); - } - } - if (camera_mode || !sam2Model.EmbeddingExist()) - { - sam2Model.ProcessEmbedding(inputImage, inputImageWidth, inputImageHeight); - } - sam2Model.ProcessMask(inputImage, inputImageWidth, inputImageHeight); - result = sam2Model.success; - } - - if (!result) - { - oneshot = false; - return; - } - - // convert result to image - Color32[] outputImage; - int outputWidth, - outputHeight; - outputImage = sam2Model.visualizedResult.GetPixels32(); - outputWidth = sam2Model.visualizedResult.width; - outputHeight = sam2Model.visualizedResult.height; - - long end_time2 = DateTime.UtcNow.Ticks / TimeSpan.TicksPerMillisecond; - - if (label_text != null) - { - label_text.text = - ((end_time - start_time) + (end_time2 - start_time2)).ToString() - + "ms\n" - + envName; - } - - // for viewer - if (originalTexture == null) - { - originalTexture = new Texture2D( - outputWidth, - outputHeight, - TextureFormat.RGBA32, - false - ); - } - if (labelTexture == null) - { - labelTexture = new Texture2D( - outputWidth, - outputHeight, - TextureFormat.RGBA32, - false - ); - } - originalTexture.SetPixels32(inputImage); - originalTexture.Apply(); - raw_image.texture = originalTexture; - blendMaterial.SetTexture(mainTexId, originalTexture); - - labelTexture.SetPixels32(outputImage); - labelTexture.Apply(); - blendMaterial.SetTexture(blendTexId, labelTexture); - - blendMaterial.SetFloat(mainVFlipId, 1); //originalTexture is Top2Bottom - blendMaterial.SetFloat(blendVFlipId, 1); //outputImage is Top2Bottom - - float rawImageRatio = rawImageSize.x / rawImageSize.y; - float ratio = inputImageWidth / (float)inputImageHeight; - raw_image.rectTransform.sizeDelta = new Vector2( - ratio / rawImageRatio * rawImageSize.x, - rawImageSize.y - ); - - raw_image.gameObject.SetActive(true); - - oneshot = false; - } - - // Download models and Create ailiaModel - void CreateAiliaNet(ImageSegmentaion2Models modelType, bool gpu_mode = true) - { - AiliaDownload ailia_download = new AiliaDownload(); - ailia_download.DownloaderProgressPanel = UICanvas.transform - .Find("DownloaderProgressPanel") - .gameObject; - List urlList = null; - - if (ImageSegmentaion2Models == ImageSegmentaion2Models.image_encoder_hiera_l) - { - sam2Model = new SegmentAnything2Model(); - urlList = sam2Model.GetModelURLs(ImageSegmentaion2Models); - } - - StartCoroutine( - ailia_download.DownloadWithProgressFromURL( - urlList, - () => - { - if ( - ImageSegmentaion2Models == ImageSegmentaion2Models.image_encoder_hiera_l - ) - { - modelPrepared = sam2Model.InitializeModels( - ImageSegmentaion2Models, - gpu_mode - ); - envName = sam2Model.EnvironmentName(); - } - } - ) - ); - } - - void LoadImage( - ImageSegmentaion2Models ImageSegmentaion2Models, - AiliaImageSource ailiaImageSource - ) - { - switch (ImageSegmentaion2Models) - { - case ImageSegmentaion2Models.image_encoder_hiera_l: - ailiaImageSource.CreateSource(image_source_sam2); - break; - } - } - - void HandleClick(bool leftClick, bool rightClick, bool middleClick) - { - if (!raw_image.isActiveAndEnabled || raw_image.texture == null) - { - return; - } - - Vector3[] corners = new Vector3[4]; - raw_image.rectTransform.GetWorldCorners(corners); - - Rect rawImageRect = new Rect( - corners[0].x, - Screen.height - corners[2].y, - corners[2].x - corners[0].x, - corners[2].y - corners[0].y - ); - - Vector2 mousePos = new Vector2(Input.mousePosition.x, Input.mousePosition.y); - - float widthRatio = raw_image.texture.width / rawImageRect.width; - float heightRatio = raw_image.texture.height / rawImageRect.height; - - int x = Mathf.Clamp( - Mathf.RoundToInt((mousePos.x - rawImageRect.x) * widthRatio), - 0, - raw_image.texture.width - 1 - ); - int y = - raw_image.texture.height - - 1 - - Mathf.Clamp( - Mathf.RoundToInt((mousePos.y - rawImageRect.y) * heightRatio), - 0, - raw_image.texture.height - 1 - ); - - if (rawImageRect.Contains(mousePos)) - { - if (leftClick || rightClick) - { - sam2Model?.AddClickPoint(x, y, rightClick); - oneshot = true; - - Debug.Log($"Click registered at: {x}, {y}"); - } - - if (middleClick && !isDraggingForBox) - { - isDraggingForBox = true; - boxRect.xMin = x; - boxRect.yMin = y; - } - } - - if (!middleClick && isDraggingForBox) - { - isDraggingForBox = false; - - float firstX = boxRect.xMin; - float firstY = boxRect.yMin; - - boxRect.xMin = Math.Min(firstX, x); - boxRect.yMin = Math.Min(firstY, y); - boxRect.xMax = Math.Max(firstX, x); - boxRect.yMax = Math.Max(firstY, y); - - sam2Model.SetBoxCoords(boxRect); - oneshot = true; - } - } - - private void OnGUI() - { - if (!raw_image.isActiveAndEnabled || raw_image.texture == null) - { - return; - } - - if ((boxRect.width > 0 && boxRect.height > 0) || isDraggingForBox) - { - Vector3[] corners = new Vector3[4]; - raw_image.rectTransform.GetWorldCorners(corners); - - Rect rawImageRect = new Rect( - corners[0].x, - Screen.height - corners[2].y, - corners[2].x - corners[0].x, - corners[2].y - corners[0].y - ); - - float widthRatio = raw_image.texture.width / rawImageRect.width; - float heightRatio = raw_image.texture.height / rawImageRect.height; - - int xMin = (int)(boxRect.xMin / widthRatio + rawImageRect.x); - int yMin = (int)(boxRect.yMin / heightRatio + rawImageRect.y); - int xMax = ( - (int)( - isDraggingForBox - ? Input.mousePosition.x - : (boxRect.xMax / widthRatio + rawImageRect.x) - ) - ); - int yMax = ( - (int)( - isDraggingForBox - ? 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forceMaximumCompressionQuality_BC6H_BC7: 0 - - serializedVersion: 3 - buildTarget: Android - maxTextureSize: 2048 - resizeAlgorithm: 0 - textureFormat: -1 - textureCompression: 1 - compressionQuality: 50 - crunchedCompression: 0 - allowsAlphaSplitting: 0 - overridden: 0 - androidETC2FallbackOverride: 0 - forceMaximumCompressionQuality_BC6H_BC7: 0 - - serializedVersion: 3 - buildTarget: iPhone - maxTextureSize: 2048 - resizeAlgorithm: 0 - textureFormat: -1 - textureCompression: 1 - compressionQuality: 50 - crunchedCompression: 0 - allowsAlphaSplitting: 0 - overridden: 0 - androidETC2FallbackOverride: 0 - forceMaximumCompressionQuality_BC6H_BC7: 0 - - serializedVersion: 3 - buildTarget: WebGL - maxTextureSize: 2048 - resizeAlgorithm: 0 - textureFormat: -1 - textureCompression: 1 - compressionQuality: 50 - crunchedCompression: 0 - allowsAlphaSplitting: 0 - overridden: 0 - androidETC2FallbackOverride: 0 - forceMaximumCompressionQuality_BC6H_BC7: 0 - spriteSheet: - serializedVersion: 2 - sprites: [] - outline: [] - physicsShape: [] - bones: [] - spriteID: - internalID: 0 - vertices: [] - indices: - edges: [] - weights: [] - secondaryTextures: [] - nameFileIdTable: {} - spritePackingTag: - pSDRemoveMatte: 0 - pSDShowRemoveMatteOption: 0 - userData: - assetBundleName: - assetBundleVariant: From 4ee693f48b734ad6de0600da59c91b2ddcbce4ba Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?=E3=82=AD=E3=83=A7=E3=83=BB=E3=83=AA=E3=83=BC=E3=82=B7?= =?UTF-8?q?=E3=83=A5=E3=83=B3?= Date: Tue, 17 Jun 2025 15:52:39 +0900 Subject: [PATCH 08/16] Remove debug log --- .../AILIA-MODELS/ImageSegmentation/SegmentAnything2Model.cs | 5 ----- 1 file changed, 5 deletions(-) diff --git a/Assets/AXIP/AILIA-MODELS/ImageSegmentation/SegmentAnything2Model.cs b/Assets/AXIP/AILIA-MODELS/ImageSegmentation/SegmentAnything2Model.cs index 2ce60796..4b5ec80b 100644 --- a/Assets/AXIP/AILIA-MODELS/ImageSegmentation/SegmentAnything2Model.cs +++ b/Assets/AXIP/AILIA-MODELS/ImageSegmentation/SegmentAnything2Model.cs @@ -899,11 +899,6 @@ float[] pointLabels flattenedCoords[i * 2 + 1] = scaledCoords[i, 1]; } - for (int i = 0; i < flattenedCoords.Length; i++) - { - Debug.Log(flattenedCoords[i]); - } - // float[,,] maskInputDummy; float[] maskInputDummy; float[] masksEnable; From 82d67d8149ad90df45822d51ba681bca1259085c Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?=E3=82=AD=E3=83=A7=E3=83=BB=E3=83=AA=E3=83=BC=E3=82=B7?= =?UTF-8?q?=E3=83=A5=E3=83=B3?= Date: Wed, 18 Jun 2025 13:58:00 +0900 Subject: [PATCH 09/16] Error handling added --- .../SegmentAnything2Model.cs | 23 +++++++++++-------- 1 file changed, 13 insertions(+), 10 deletions(-) diff --git a/Assets/AXIP/AILIA-MODELS/ImageSegmentation/SegmentAnything2Model.cs b/Assets/AXIP/AILIA-MODELS/ImageSegmentation/SegmentAnything2Model.cs index 4b5ec80b..1c2ecfd1 100644 --- a/Assets/AXIP/AILIA-MODELS/ImageSegmentation/SegmentAnything2Model.cs +++ b/Assets/AXIP/AILIA-MODELS/ImageSegmentation/SegmentAnything2Model.cs @@ -293,13 +293,13 @@ private float[] GetPointLabels() // Run Embedding private void RunEmbedding(Color32[] image, int imgWidth, int imgHeight) { - if (isQuitting || !modelsInitialized || encoder == null || decoder == null) + if (isQuitting || !modelsInitialized || encoder == null) { return; } float[,,,] inputTensor = PreprocessImage(image, imgWidth, imgHeight, targetSize); - float[] nchw = Flatten4D(inputTensor); + float[] nchwInput = Flatten4D(inputTensor); try { @@ -325,7 +325,7 @@ private void RunEmbedding(Color32[] image, int imgWidth, int imgHeight) return; } - bool dataSetResult = encoder.SetInputBlobData(nchw, imgIndex); + bool dataSetResult = encoder.SetInputBlobData(nchwInput, imgIndex); // Debug.Log($"updated SET DATA {dataSetResult}"); bool encResult = encoder.Update(); @@ -875,9 +875,7 @@ private struct BackboneOutputs float[] pointLabels ) { - if ( - isQuitting || !modelsInitialized || encoder == null || decoder == null || prompt == null - ) + if (isQuitting || !modelsInitialized || decoder == null || prompt == null) { return (new bool[0][,], new float[0]); } @@ -905,7 +903,12 @@ float[] pointLabels // if (maskInput == null) // { - maskInputDummy = new float[1 * 256 * 256]; + int maskInputDummyChannel = 1; + int maskInputDummyHeight = 256; + int maskInputDummyWidth = 256; + maskInputDummy = new float[ + maskInputDummyChannel * maskInputDummyHeight * maskInputDummyWidth + ]; // maskInputDummy = new float[1, 256, 256]; masksEnable = new float[1] { 0f }; // } @@ -943,9 +946,9 @@ float[] pointLabels ailia.Ailia.AILIAShape masksShape = new ailia.Ailia.AILIAShape(); masksShape.dim = 3; - masksShape.z = 1; - masksShape.y = 256; - masksShape.x = 256; + masksShape.z = (uint)maskInputDummyChannel; + masksShape.y = (uint)maskInputDummyHeight; + masksShape.x = (uint)maskInputDummyWidth; ailia.Ailia.AILIAShape masksEnableShape = new ailia.Ailia.AILIAShape(); masksEnableShape.dim = 1; From de6860567132accac5c974c52e9c0b089d5038ec Mon Sep 17 00:00:00 2001 From: Kazuki Kyakuno Date: Tue, 24 Jun 2025 17:32:30 +0900 Subject: [PATCH 10/16] Added license file --- .../LICENSE/SEGMENT_ANYTHING2_LICENSE | 201 ++++++++++++++++++ .../LICENSE/SEGMENT_ANYTHING2_LICENSE.meta | 7 + 2 files changed, 208 insertions(+) create mode 100644 Assets/AXIP/AILIA-MODELS/ImageSegmentation/LICENSE/SEGMENT_ANYTHING2_LICENSE create mode 100644 Assets/AXIP/AILIA-MODELS/ImageSegmentation/LICENSE/SEGMENT_ANYTHING2_LICENSE.meta diff --git a/Assets/AXIP/AILIA-MODELS/ImageSegmentation/LICENSE/SEGMENT_ANYTHING2_LICENSE b/Assets/AXIP/AILIA-MODELS/ImageSegmentation/LICENSE/SEGMENT_ANYTHING2_LICENSE new file mode 100644 index 00000000..261eeb9e --- /dev/null +++ b/Assets/AXIP/AILIA-MODELS/ImageSegmentation/LICENSE/SEGMENT_ANYTHING2_LICENSE @@ -0,0 +1,201 @@ + Apache License + Version 2.0, January 2004 + http://www.apache.org/licenses/ + + TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION + + 1. 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We also recommend that a + file or class name and description of purpose be included on the + same "printed page" as the copyright notice for easier + identification within third-party archives. + + Copyright [yyyy] [name of copyright owner] + + Licensed under the Apache License, Version 2.0 (the "License"); + you may not use this file except in compliance with the License. + You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + + Unless required by applicable law or agreed to in writing, software + distributed under the License is distributed on an "AS IS" BASIS, + WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + See the License for the specific language governing permissions and + limitations under the License. diff --git a/Assets/AXIP/AILIA-MODELS/ImageSegmentation/LICENSE/SEGMENT_ANYTHING2_LICENSE.meta b/Assets/AXIP/AILIA-MODELS/ImageSegmentation/LICENSE/SEGMENT_ANYTHING2_LICENSE.meta new file mode 100644 index 00000000..f8737900 --- /dev/null +++ b/Assets/AXIP/AILIA-MODELS/ImageSegmentation/LICENSE/SEGMENT_ANYTHING2_LICENSE.meta @@ -0,0 +1,7 @@ +fileFormatVersion: 2 +guid: 55b9580dcf6d34bd39eca3658b4f7f4e +DefaultImporter: + externalObjects: {} + userData: + assetBundleName: + assetBundleVariant: From 7d17ccde393d1fa5d052d321c2e817b3e71266bd Mon Sep 17 00:00:00 2001 From: Kazuki Kyakuno Date: Tue, 24 Jun 2025 17:34:47 +0900 Subject: [PATCH 11/16] Add model to list --- .../{SEGMENT_ANYTHING2_LICENSE => SEGMENT_ANYTHING_2_LICENSE} | 0 ...NT_ANYTHING2_LICENSE.meta => SEGMENT_ANYTHING_2_LICENSE.meta} | 0 README.md | 1 + 3 files changed, 1 insertion(+) rename Assets/AXIP/AILIA-MODELS/ImageSegmentation/LICENSE/{SEGMENT_ANYTHING2_LICENSE => SEGMENT_ANYTHING_2_LICENSE} (100%) rename Assets/AXIP/AILIA-MODELS/ImageSegmentation/LICENSE/{SEGMENT_ANYTHING2_LICENSE.meta => SEGMENT_ANYTHING_2_LICENSE.meta} (100%) diff --git a/Assets/AXIP/AILIA-MODELS/ImageSegmentation/LICENSE/SEGMENT_ANYTHING2_LICENSE b/Assets/AXIP/AILIA-MODELS/ImageSegmentation/LICENSE/SEGMENT_ANYTHING_2_LICENSE similarity index 100% rename from Assets/AXIP/AILIA-MODELS/ImageSegmentation/LICENSE/SEGMENT_ANYTHING2_LICENSE rename to Assets/AXIP/AILIA-MODELS/ImageSegmentation/LICENSE/SEGMENT_ANYTHING_2_LICENSE diff --git a/Assets/AXIP/AILIA-MODELS/ImageSegmentation/LICENSE/SEGMENT_ANYTHING2_LICENSE.meta b/Assets/AXIP/AILIA-MODELS/ImageSegmentation/LICENSE/SEGMENT_ANYTHING_2_LICENSE.meta similarity index 100% rename from Assets/AXIP/AILIA-MODELS/ImageSegmentation/LICENSE/SEGMENT_ANYTHING2_LICENSE.meta rename to Assets/AXIP/AILIA-MODELS/ImageSegmentation/LICENSE/SEGMENT_ANYTHING_2_LICENSE.meta diff --git a/README.md b/README.md index 951a1ba5..b2880214 100644 --- a/README.md +++ b/README.md @@ -77,6 +77,7 @@ The collection of pre-trained, state-of-the-art models for Unity. | [pspnet-hair-segmentation](/Assets/AXIP/AILIA-MODELS/ImageSegmentation/) | [pytorch-hair-segmentation](https://github.com/YBIGTA/pytorch-hair-segmentation) | Pytorch | 1.2.2 and later || | [U2net](/Assets/AXIP/AILIA-MODELS/ImageSegmentation/) | [U2-Net: Going Deeper with Nested U-Structure for Salient Object Detection](https://github.com/xuebinqin/U-2-Net) | Pytorch | 1.2.2 and later | [EN](https://medium.com/axinc-ai/u2net-a-machine-learning-model-that-performs-object-cropping-in-a-single-shot-48adfc158483) [JP](https://medium.com/axinc/u2net-%E3%82%B7%E3%83%B3%E3%82%B0%E3%83%AB%E3%82%B7%E3%83%A7%E3%83%83%E3%83%88%E3%81%A7%E7%89%A9%E4%BD%93%E3%81%AE%E5%88%87%E3%82%8A%E6%8A%9C%E3%81%8D%E3%82%92%E8%A1%8C%E3%81%86%E6%A9%9F%E6%A2%B0%E5%AD%A6%E7%BF%92%E3%83%A2%E3%83%87%E3%83%AB-e346f2787cdb) | | [segment-anything](/Assets/AXIP/AILIA-MODELS/ImageSegmentation/) | [Segment Anything](https://github.com/facebookresearch/segment-anything) | Pytorch | 1.2.16 and later | +| [segment-anything-2](/Assets/AXIP/AILIA-MODELS/ImageSegmentation/) | [Segment Anything 2](https://github.com/facebookresearch/segment-anything-2) | Pytorch | 1.2.16 and later | ## Image manipulation From b1e7e3b1da03929159f20da78610499aad3fd72e Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?=E3=82=AD=E3=83=A7=E3=83=BB=E3=83=AA=E3=83=BC=E3=82=B7?= =?UTF-8?q?=E3=83=A5=E3=83=B3?= Date: Wed, 25 Jun 2025 14:29:06 +0900 Subject: [PATCH 12/16] Remove unnecessary comments --- .../SegmentAnything2Model.cs | 106 ------------------ 1 file changed, 106 deletions(-) diff --git a/Assets/AXIP/AILIA-MODELS/ImageSegmentation/SegmentAnything2Model.cs b/Assets/AXIP/AILIA-MODELS/ImageSegmentation/SegmentAnything2Model.cs index 1c2ecfd1..50d6b7de 100644 --- a/Assets/AXIP/AILIA-MODELS/ImageSegmentation/SegmentAnything2Model.cs +++ b/Assets/AXIP/AILIA-MODELS/ImageSegmentation/SegmentAnything2Model.cs @@ -24,13 +24,6 @@ public class SegmentAnything2Model private const string promptWeightPath = "prompt_encoder_hiera_l.onnx"; private const string promptProtoPath = "prompt_encoder_hiera_l.onnx.prototxt"; - // private const string memAttentionWeightPath = "memory_attention_hiera_l.opt.onnx"; - // private const string memAttentionProtoPath = "memory_attention_hiera_l.opt.onnx.prototxt"; - // private const string encoderMemWeightPath = "memory_encoder_hiera_l.onnx"; - // private const string encoderMemProtoPath = "memory_encoder_hiera_l.onnx.prototxt"; - // private const string mlpWeightPath = "mlp_hiera_l.onnx"; - // private const string mlpProtoPath = "mlp_hiera_l.onnx.prototxt"; - private List clickPoints = new(); private List clickPointLabels = new(); private Rect boxCoords = new(); @@ -103,30 +96,12 @@ public List GetModelURLs(ImageSegmentaionModels modelType) modelDownloadURLs.Add( new ModelDownloadURL() { folder_path = serverFolderName, file_name = decoderProtoPath } ); - // modelDownloadURLs.Add( - // new ModelDownloadURL() { folder_path = serverFolderName, file_name = memAttentionWeightPath } - // ); - // modelDownloadURLs.Add( - // new ModelDownloadURL() { folder_path = serverFolderName, file_name = memAttentionProtoPath } - // ); - // modelDownloadURLs.Add( - // new ModelDownloadURL() { folder_path = serverFolderName, file_name = encoderMemWeightPath } - // ); - // modelDownloadURLs.Add( - // new ModelDownloadURL() { folder_path = serverFolderName, file_name = encoderMemProtoPath } - // ); modelDownloadURLs.Add( new ModelDownloadURL() { folder_path = serverFolderName, file_name = promptWeightPath } ); modelDownloadURLs.Add( new ModelDownloadURL() { folder_path = serverFolderName, file_name = promptProtoPath } ); - // modelDownloadURLs.Add( - // new ModelDownloadURL() { folder_path = serverFolderName, file_name = mlpWeightPath } - // ); - // modelDownloadURLs.Add( - // new ModelDownloadURL() { folder_path = serverFolderName, file_name = mlpProtoPath } - // ); return modelDownloadURLs; } @@ -155,22 +130,6 @@ public bool InitializeModels(ImageSegmentaionModels modelType, bool gpuMode) Application.temporaryCachePath, decoderProtoPath ); - // string memAttPath = System.IO.Path.Combine( - // Application.temporaryCachePath, - // memAttentionWeightPath - // ); - // string memAttProtoPath = System.IO.Path.Combine( - // Application.temporaryCachePath, - // memAttentionProtoPath - // ); - // string encMemPath = System.IO.Path.Combine( - // Application.temporaryCachePath, - // encoderMemWeightPath - // ); - // string encMemProtoPath = System.IO.Path.Combine( - // Application.temporaryCachePath, - // encoderMemProtoPath - // ); string pmtPath = System.IO.Path.Combine( Application.temporaryCachePath, promptWeightPath @@ -179,21 +138,10 @@ public bool InitializeModels(ImageSegmentaionModels modelType, bool gpuMode) Application.temporaryCachePath, promptProtoPath ); - // string mlpPath = System.IO.Path.Combine( - // Application.temporaryCachePath, - // mlpWeightPath - // ); - // string mlpProPath = System.IO.Path.Combine( - // Application.temporaryCachePath, - // mlpProtoPath - // ); encoder = new ailia.AiliaModel(); decoder = new ailia.AiliaModel(); - // memAttention = new ailia.AiliaModel(); - // encoderMem = new ailia.AiliaModel(); prompt = new ailia.AiliaModel(); - // mlp = new ailia.AiliaModel(); uint memory_mode = ailia.Ailia.AILIA_MEMORY_REDUCE_CONSTANT @@ -202,35 +150,23 @@ public bool InitializeModels(ImageSegmentaionModels modelType, bool gpuMode) memory_mode = ailia.Ailia.AILIA_MEMORY_REDUCE_INTERSTAGE; encoder.SetMemoryMode(memory_mode); decoder.SetMemoryMode(memory_mode); - // memAttention.SetMemoryMode(memory_mode); - // encoderMem.SetMemoryMode(memory_mode); prompt.SetMemoryMode(memory_mode); - // mlp.SetMemoryMode(memory_mode); this.gpuMode = gpuMode; if (gpuMode) { encoder.Environment(ailia.Ailia.AILIA_ENVIRONMENT_TYPE_GPU); decoder.Environment(ailia.Ailia.AILIA_ENVIRONMENT_TYPE_GPU); - // memAttention.Environment(ailia.Ailia.AILIA_ENVIRONMENT_TYPE_GPU); - // encoderMem.Environment(ailia.Ailia.AILIA_ENVIRONMENT_TYPE_GPU); prompt.Environment(ailia.Ailia.AILIA_ENVIRONMENT_TYPE_GPU); - // mlp.Environment(ailia.Ailia.AILIA_ENVIRONMENT_TYPE_GPU); } bool encOpened = false; bool decOpened = false; - // bool memOpened = false; - // bool encMemOpened = false; bool promptOpened = false; - // bool mlpOpened = false; encOpened = encoder.OpenFile(encProtoPath, encPath); decOpened = decoder.OpenFile(decProtoPath, decPath); - // memOpened = memAttention.OpenFile(memAttProtoPath, memAttPath); - // encMemOpened = encoderMem.OpenFile(encMemProtoPath, encMemPath); promptOpened = prompt.OpenFile(pmtProtoPath, pmtPath); - // mlpOpened = mlp.OpenFile(mlpProPath, mlpPath); if (!encOpened || !decOpened || !promptOpened) { @@ -515,7 +451,6 @@ private void RunEmbedding(Color32[] image, int imgWidth, int imgHeight) float[][,,] visionFeats = PrepareBackboneFeatures(backboneData); - // no_mem_embed = self.trunc_normal((1, 1, 256), std=0.02).astype(np.float32) int hidden_dim = 256; float[,,] noMemEmbed = TruncNormal(1, 1, hidden_dim, 0.02f); float[,,] lastFeat = visionFeats[visionFeats.Length - 1]; @@ -529,10 +464,6 @@ private void RunEmbedding(Color32[] image, int imgWidth, int imgHeight) (64, 64) }; - // feats = [ - // np.transpose(feat, (1, 2, 0)).reshape(1, -1, *feat_size) - // for feat, feat_size in zip(vision_feats[::-1], bb_feat_sizes[::-1]) - // ][::-1] float[][,,,] featsArray = new float[visionFeats.Length][,,,]; for (int i = 0; i < visionFeats.Length; i++) { @@ -573,7 +504,6 @@ private void RunEmbedding(Color32[] image, int imgWidth, int imgHeight) } Array.Reverse(featsArray); - // features = {"image_embed": feats[-1], "high_res_feats": feats[:-1]} float[,,,] lastFeatElement = featsArray[featsArray.Length - 1]; @@ -636,25 +566,6 @@ private void RunEmbedding(Color32[] image, int imgWidth, int imgHeight) int numFeatureLevels = 3; float[][,,,] featureMaps = backboneData.backboneFpn.TakeLast(numFeatureLevels).ToArray(); - // for (int i = 0; i < featureMaps.Length; i++) - // { - // Debug.Log(featureMaps[i].Length); - // } - // float[][] visionPosEmbeds = backboneData.visionPosEnc.TakeLast(numFeatureLevels).ToArray(); - - // float[][,,,] visionPosEmbeds4D = new float[3][,,,] - // { - // ReshapeTo4D(visionPosEmbeds[0], 1, 256, 256, 256), - // ReshapeTo4D(visionPosEmbeds[1], 1, 256, 128, 128), - // ReshapeTo4D(visionPosEmbeds[2], 1, 256, 64, 64) - // }; - - // float[][,,,] featureMaps4D = new float[3][,,,] - // { - // ReshapeTo4D(featureMaps[0], 1, 128, 128, 128), - // ReshapeTo4D(featureMaps[1], 1, 256, 64, 64), - // ReshapeTo4D(featureMaps[2], 1, 256, 64, 64) - // }; float[][,,] visionFeats = new float[numFeatureLevels][,,]; @@ -686,12 +597,6 @@ private void RunEmbedding(Color32[] image, int imgWidth, int imgHeight) visionFeats[i] = output; } - // (int, int)[] feat_sizes = visionPosEmbeds4D - // .Select(x => (height: x.GetLength(2), width: x.GetLength(3))) - // .ToArray(); - - // float[][,,] processed = ProcessVisionPosEmbeds(visionPosEmbeds4D); - return visionFeats; } @@ -897,26 +802,16 @@ float[] pointLabels flattenedCoords[i * 2 + 1] = scaledCoords[i, 1]; } - // float[,,] maskInputDummy; float[] maskInputDummy; float[] masksEnable; - // if (maskInput == null) - // { int maskInputDummyChannel = 1; int maskInputDummyHeight = 256; int maskInputDummyWidth = 256; maskInputDummy = new float[ maskInputDummyChannel * maskInputDummyHeight * maskInputDummyWidth ]; - // maskInputDummy = new float[1, 256, 256]; masksEnable = new float[1] { 0f }; - // } - // else - // { - // maskInputDummy = maskInput; - // masksEnable = new int[] { 1 }; - // } int promptCoordsIndex = prompt.FindBlobIndexByName("coords"); int promptLabelsIndex = prompt.FindBlobIndexByName("labels"); @@ -1241,7 +1136,6 @@ float[] pointLabels return (new bool[0][,], new float[0]); } - // masks, iou_pred, sam_tokens_out, object_score_logits = mask_decoder.run int masksBlobIndex = decoder.FindBlobIndexByName("masks"); int iouPredBlobIndex = decoder.FindBlobIndexByName("iou_pred"); int samTokensOutBlobIndex = decoder.FindBlobIndexByName("sam_tokens_out"); From 494e5fdcbbfb8242dbb4c3cac05ffea032b524af Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?=E3=82=AD=E3=83=A7=E3=83=BB=E3=83=AA=E3=83=BC=E3=82=B7?= =?UTF-8?q?=E3=83=A5=E3=83=B3?= Date: Wed, 25 Jun 2025 15:41:47 +0900 Subject: [PATCH 13/16] Fix the image and coordinate ratio not mismatch --- .../SegmentAnything2Model.cs | 36 ++----------------- 1 file changed, 3 insertions(+), 33 deletions(-) diff --git a/Assets/AXIP/AILIA-MODELS/ImageSegmentation/SegmentAnything2Model.cs b/Assets/AXIP/AILIA-MODELS/ImageSegmentation/SegmentAnything2Model.cs index 50d6b7de..37fc807f 100644 --- a/Assets/AXIP/AILIA-MODELS/ImageSegmentation/SegmentAnything2Model.cs +++ b/Assets/AXIP/AILIA-MODELS/ImageSegmentation/SegmentAnything2Model.cs @@ -1205,31 +1205,6 @@ float[] pointLabels return (new bool[0][,], new float[0]); } - float[,,,] masks = ReshapeTo4D( - masksBlobOutput, - (int)masksBlobShape.w, - (int)masksBlobShape.z, - (int)masksBlobShape.y, - (int)masksBlobShape.x - ); - - float[,] iouPred = ReshapeTo2D( - iouPredBlobOutput, - (int)iouPredBlobShape.y, - (int)iouPredBlobShape.x - ); - float[,,] samTokens = ReshapeTo3D( - samTokensOutBlobOutput, - (int)samTokensOutBlobShape.z, - (int)samTokensOutBlobShape.y, - (int)samTokensOutBlobShape.x - ); - float[,] objectScore = ReshapeTo2D( - objectScoreLogitsBlobOutput, - (int)objectScoreLogitsBlobShape.y, - (int)objectScoreLogitsBlobShape.x - ); - if (isQuitting || decoder == null) { return (new bool[0][,], new float[0]); @@ -1297,13 +1272,12 @@ float[] pointLabels // Scale coordinates to target size private float[,] ApplyCoordinateScaling(float[,] coords, int imgHeight, int imgWidth) { - float scale = GetScale(imgWidth, imgHeight); float[,] scaledCoords = new float[coords.GetLength(0), coords.GetLength(1)]; for (int i = 0; i < coords.GetLength(0); i++) { - scaledCoords[i, 0] = coords[i, 0] * scale; - scaledCoords[i, 1] = coords[i, 1] * scale; + scaledCoords[i, 0] = coords[i, 0] * targetSize / imgWidth; + scaledCoords[i, 1] = coords[i, 1] * targetSize / imgHeight; } return scaledCoords; @@ -1458,17 +1432,13 @@ int imageSize // Convert Color32[] to float[height, width, channels] float[,,] floatImage = Color32ArrayToFloatArray(resizedImage, newHeight, newWidth); - // Normalize per channel (subtract mean, divide std) - float[] mean = new float[] { 0.485f, 0.456f, 0.406f }; - float[] std = new float[] { 0.229f, 0.224f, 0.225f }; - for (int h = 0; h < newHeight; h++) { for (int w = 0; w < newWidth; w++) { for (int c = 0; c < 3; c++) { - floatImage[h, w, c] = (floatImage[h, w, c] - mean[c]) / std[c]; + floatImage[h, w, c] = (floatImage[h, w, c] - Mean[c]) / Std[c]; } } } From 6c6a691fd566dac72f9bc8c2808adaa0b0a26a4b Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?=E3=82=AD=E3=83=A7=E3=83=BB=E3=83=AA=E3=83=BC=E3=82=B7?= =?UTF-8?q?=E3=83=A5=E3=83=B3?= Date: Wed, 25 Jun 2025 15:44:48 +0900 Subject: [PATCH 14/16] Remove unused line --- .../AXIP/AILIA-MODELS/ImageSegmentation/SegmentAnything2Model.cs | 1 - 1 file changed, 1 deletion(-) diff --git a/Assets/AXIP/AILIA-MODELS/ImageSegmentation/SegmentAnything2Model.cs b/Assets/AXIP/AILIA-MODELS/ImageSegmentation/SegmentAnything2Model.cs index 37fc807f..c67b409d 100644 --- a/Assets/AXIP/AILIA-MODELS/ImageSegmentation/SegmentAnything2Model.cs +++ b/Assets/AXIP/AILIA-MODELS/ImageSegmentation/SegmentAnything2Model.cs @@ -1418,7 +1418,6 @@ int imageSize ) { // Resize image to (imageSize, imageSize) - float scale = GetScale(originalWidth, originalHeight); int newWidth = imageSize; int newHeight = imageSize; Color32[] resizedImage = ResizeColor32( From 35a338f1801ddc47b4a736a6bf6ae5c908f6879a Mon Sep 17 00:00:00 2001 From: Kazuki Kyakuno Date: Fri, 11 Jul 2025 08:58:17 +0900 Subject: [PATCH 15/16] Fix box mode --- .../ImageSegmentation/AiliaImageSegmentationSample.cs | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/Assets/AXIP/AILIA-MODELS/ImageSegmentation/AiliaImageSegmentationSample.cs b/Assets/AXIP/AILIA-MODELS/ImageSegmentation/AiliaImageSegmentationSample.cs index a15d7451..39488bbd 100644 --- a/Assets/AXIP/AILIA-MODELS/ImageSegmentation/AiliaImageSegmentationSample.cs +++ b/Assets/AXIP/AILIA-MODELS/ImageSegmentation/AiliaImageSegmentationSample.cs @@ -457,8 +457,8 @@ void HandleClick(bool leftClick, bool rightClick, bool middleClick) boxRect.xMax = Math.Max(firstX, x); boxRect.yMax = Math.Max(firstY, y); - samModel.SetBoxCoords(boxRect); - sam2Model.SetBoxCoords(boxRect); + samModel?.SetBoxCoords(boxRect); + sam2Model?.SetBoxCoords(boxRect); oneshot = true; } } From 06cb718b030be764669a1375eaee10cd79cbfbd6 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?=E3=82=AD=E3=83=A7=E3=83=BB=E3=83=AA=E3=83=BC=E3=82=B7?= =?UTF-8?q?=E3=83=A5=E3=83=B3?= Date: Tue, 22 Jul 2025 10:09:15 +0900 Subject: [PATCH 16/16] Fix accuracy problem --- .../SegmentAnything2Model.cs | 127 +++++++++++++----- 1 file changed, 90 insertions(+), 37 deletions(-) diff --git a/Assets/AXIP/AILIA-MODELS/ImageSegmentation/SegmentAnything2Model.cs b/Assets/AXIP/AILIA-MODELS/ImageSegmentation/SegmentAnything2Model.cs index c67b409d..d4dabb3f 100644 --- a/Assets/AXIP/AILIA-MODELS/ImageSegmentation/SegmentAnything2Model.cs +++ b/Assets/AXIP/AILIA-MODELS/ImageSegmentation/SegmentAnything2Model.cs @@ -1210,23 +1210,18 @@ float[] pointLabels return (new bool[0][,], new float[0]); } - int numMasks = (int)iouPredBlobShape.x; - int maskWidth = (int)masksBlobShape.x; - int maskHeight = (int)masksBlobShape.y; - int maskArea = maskWidth * maskHeight; - bool[][,] masksResult = new bool[numMasks][,]; - - for (int i = 0; i < numMasks; i++) - { - float[,,,] maskTensor = ReshapeToTensor( + float[,,,] resized = PostprocessMasks( + ReshapeTo4D( masksBlobOutput, - i, - maskHeight, - maskWidth, - maskArea - ); - masksResult[i] = PostprocessMask(maskTensor, imgHeight, imgWidth); - } + (int)masksBlobShape.w, + (int)masksBlobShape.z, + (int)masksBlobShape.y, + (int)masksBlobShape.x + ), + imgHeight, + imgWidth + ); + bool[][,] masksResult = ConvertToBoolMasks(resized); return (masksResult, iouPredBlobOutput); } @@ -1506,40 +1501,98 @@ int dstHeight return output; } - private bool[,] PostprocessMask(float[,,,] mask, int origHeight, int origWidth) + private float[,] ResizeBilinear(float[,] src, int targetHeight, int targetWidth) { - int maskHeight = mask.GetLength(2); - int maskWidth = mask.GetLength(3); + int srcHeight = src.GetLength(0); + int srcWidth = src.GetLength(1); - // Final resize to targetSize - bool[,] finalMask = new bool[origHeight, origWidth]; + float[,] result = new float[targetHeight, targetWidth]; - for (int y = 0; y < origHeight; y++) + float scaleY = (float)(srcHeight - 1) / (targetHeight - 1); + float scaleX = (float)(srcWidth - 1) / (targetWidth - 1); + + for (int y = 0; y < targetHeight; y++) { - float srcY = y * maskHeight / origHeight; + float srcY = y * scaleY; int y0 = (int)Math.Floor(srcY); - int y1 = Math.Min(y0 + 1, maskHeight - 1); - float wy = srcY - y0; + int y1 = Math.Min(y0 + 1, srcHeight - 1); + float dy = srcY - y0; - for (int x = 0; x < origWidth; x++) + for (int x = 0; x < targetWidth; x++) { - float srcX = x * maskWidth / origWidth; + float srcX = x * scaleX; int x0 = (int)Math.Floor(srcX); - int x1 = Math.Min(x0 + 1, maskWidth - 1); - float wx = srcX - x0; + int x1 = Math.Min(x0 + 1, srcWidth - 1); + float dx = srcX - x0; + + float top = (1 - dx) * src[y0, x0] + dx * src[y0, x1]; + float bottom = (1 - dx) * src[y1, x0] + dx * src[y1, x1]; + result[y, x] = (1 - dy) * top + dy * bottom; + } + } + + return result; + } + + private float[,,,] PostprocessMasks(float[,,,] masks, int targetHeight, int targetWidth) + { + int batch = masks.GetLength(0); + int channels = masks.GetLength(1); + int height = masks.GetLength(2); + int width = masks.GetLength(3); + + float[,,,] resizedMasks = new float[batch, channels, targetHeight, targetWidth]; - // Bilinear interpolation - float val = - (1 - wy) * (1 - wx) * mask[0, 0, y0, x0] - + wy * (1 - wx) * mask[0, 0, y1, x0] - + (1 - wy) * wx * mask[0, 0, y0, x1] - + wy * wx * mask[0, 0, y1, x1]; + for (int n = 0; n < batch; n++) + { + for (int c = 0; c < channels; c++) + { + // Extract 2D mask + float[,] mask2D = new float[height, width]; + for (int y = 0; y < height; y++) + for (int x = 0; x < width; x++) + mask2D[y, x] = masks[n, c, y, x]; + + // Resize it + float[,] resized2D = ResizeBilinear(mask2D, targetHeight, targetWidth); + + // Store resized mask + for (int y = 0; y < targetHeight; y++) + for (int x = 0; x < targetWidth; x++) + resizedMasks[n, c, y, x] = resized2D[y, x]; + } + } - finalMask[y, x] = val > 0; + return resizedMasks; + } + + private bool[][,] ConvertToBoolMasks(float[,,,] masks, float threshold = 0.0f) + { + int batch = masks.GetLength(0); + int channels = masks.GetLength(1); + int height = masks.GetLength(2); + int width = masks.GetLength(3); + + bool[][,] result = new bool[batch * channels][,]; + int index = 0; + + for (int b = 0; b < batch; b++) + { + for (int c = 0; c < channels; c++) + { + bool[,] binaryMask = new bool[height, width]; + for (int y = 0; y < height; y++) + { + for (int x = 0; x < width; x++) + { + binaryMask[y, x] = masks[b, c, y, x] > threshold; + } + } + result[index++] = binaryMask; } } - return finalMask; + return result; } // Calculate embedding of input image