Add pipeline test case for gcp image label detection

Author: Hironsan

tests/fixtures/cassettes/pipeline_gcp_label_detection.yaml

@@ -2,11 +2,13 @@
 
 import vcr
 
-from auto_labeling_pipeline.mappings import AmazonComprehendSentimentTemplate
-from auto_labeling_pipeline.models import AmazonComprehendSentimentRequestModel
+from auto_labeling_pipeline.mappings import AmazonComprehendSentimentTemplate, GCPImageLabelDetectionTemplate
+from auto_labeling_pipeline.models import AmazonComprehendSentimentRequestModel, GCPImageLabelDetectionRequestModel
 from auto_labeling_pipeline.pipeline import pipeline
 from auto_labeling_pipeline.postprocessing import PostProcessor
 
+from .test_models import load_image_as_b64
+
 
 def test_amazon_pipeline(cassettes_path):
     with vcr.use_cassette(str(cassettes_path / 'amazon_comprehend_sentiment.yaml'),
@@ -30,3 +32,25 @@ def test_amazon_pipeline(cassettes_path):
         assert isinstance(labels, list)
         assert len(labels) == 1
         assert 'label' in labels[0]
+
+
+def test_gcp_label_detection_pipeline(data_path, cassettes_path):
+    with vcr.use_cassette(
+            str(cassettes_path / 'pipeline_gcp_label_detection.yaml'),
+            mode='once',
+            filter_query_parameters=['key']
+    ):
+        model = GCPImageLabelDetectionRequestModel(key=os.environ.get('API_KEY_GCP', ''))
+        template = GCPImageLabelDetectionTemplate()
+        b64_image = load_image_as_b64(data_path / 'images/1500x500.jpeg')
+        post_processor = PostProcessor({})
+        labels = pipeline(
+            text=b64_image,
+            request_model=model,
+            mapping_template=template,
+            post_processing=post_processor
+        )
+        labels = labels.dict()
+        assert isinstance(labels, list)
+        assert len(labels) == 1
+        assert 'label' in labels[0]