Merge branch 'main' into maxim/dlclive3

Author: maximpavliv

.github/workflows/testing.yml

@@ -53,6 +53,23 @@ jobs:
       - name: Install and test
         shell: bash -el {0}  # Important: activates the conda environment
         run: |
-          python -m pip install --upgrade pip wheel poetry
-          python -m poetry install --extras "tf" --extras "pytorch"
-          python -m poetry run dlc-live-test --nodisplay
+          conda install pytables==3.8.0 "numpy<2"
+          
+      - name: Install dependencies via Conda
+        shell: bash -el {0}
+        run: conda install -y "numpy>=1.26,<2.0"
+
+      - name: Install Poetry
+        run: pip install --upgrade pip wheel poetry
+
+      - name: Regenerate Poetry lock
+        run: poetry lock --no-cache
+
+      - name: Install project dependencies
+        run: poetry install --with dev --extras "tf" --extras "pytorch"
+          
+      - name: Run DLC Live Tests
+        run: poetry run dlc-live-test --nodisplay
+
+      - name: Run Functional Benchmark Test
+        run: poetry run pytest tests/test_benchmark_script.py

pyproject.toml

@@ -35,7 +35,9 @@ py-cpuinfo = ">=5.0.0"
 tqdm = "^4.62.3"
 pandas = ">=1.0.1,!=1.5.0"
 tables = "^3.8"
+pytest = "^8.0"
 dlclibrary = ">=0.0.6"
+
 # PyTorch models
 scipy = ">=1.9"
 timm = { version = ">=1.0.7", optional = true }

pytest.ini

@@ -0,0 +1,3 @@
+[pytest]
+markers =
+    functional: functional tests

tests/test_benchmark_script.py

@@ -0,0 +1,48 @@
+import os
+import glob
+import pathlib
+import pytest
+from dlclive import benchmark_videos, download_benchmarking_data
+from dlclive.engine import Engine
+
+@pytest.mark.functional
+def test_benchmark_script_runs(tmp_path):
+    datafolder = tmp_path / "Data-DLC-live-benchmark"
+    download_benchmarking_data(str(datafolder))
+
+    dog_models = glob.glob(str(datafolder / "dog" / "*[!avi]"))
+    dog_video = glob.glob(str(datafolder / "dog" / "*.avi"))[0]
+    mouse_models = glob.glob(str(datafolder / "mouse_lick" / "*[!avi]"))
+    mouse_video = glob.glob(str(datafolder / "mouse_lick" / "*.avi"))[0]
+
+    out_dir = tmp_path / "results"
+    out_dir.mkdir(exist_ok=True)
+
+    pixels = [100, 400] #[2500, 10000]
+    n_frames = 5
+
+    for model_path in dog_models:
+        print(f"Running dog model: {model_path}")
+        result = benchmark_videos(
+            model_path=model_path,
+            model_type="base" if Engine.from_model_path(model_path) == Engine.TENSORFLOW else "pytorch",
+            video_path=dog_video,
+            output=str(out_dir),
+            n_frames=n_frames,
+            pixels=pixels
+        )
+        print("Dog model result:", result)
+
+    for model_path in mouse_models:
+        print(f"Running mouse model: {model_path}")
+        result = benchmark_videos(
+            model_path=model_path,
+            model_type="base" if Engine.from_model_path(model_path) == Engine.TENSORFLOW else "pytorch",
+            video_path=mouse_video,
+            output=str(out_dir),
+            n_frames=n_frames,
+            pixels=pixels
+        )
+        print("Mouse model result:", result)
+
+    assert any(out_dir.iterdir())