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104 lines
3.2 KiB
Python
104 lines
3.2 KiB
Python
# built-in dependencies
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import os
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# 3rd party dependencies
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import cv2
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# project dependencies
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from deepface import DeepFace
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from deepface.modules import verification
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from deepface.commons.logger import Logger
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logger = Logger()
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threshold = verification.find_threshold(model_name="VGG-Face", distance_metric="cosine")
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def test_find_with_exact_path():
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img_path = os.path.join("dataset", "img1.jpg")
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results = DeepFace.find(img_path=img_path, db_path="dataset", silent=True, batched=True)
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assert len(results) > 0
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required_keys = set([
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"identity", "distance", "threshold", "hash",
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"target_x", "target_y", "target_w", "target_h",
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"source_x", "source_y", "source_w", "source_h"
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])
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for result in results:
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assert isinstance(result, list)
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found_image_itself = False
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for face in result:
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assert isinstance(face, dict)
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assert set(face.keys()) == required_keys
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if face["identity"] == img_path:
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# validate reproducability
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assert face["distance"] < threshold
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# one is img1.jpg itself
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found_image_itself = True
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assert found_image_itself
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assert len(results[0]) > 1
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logger.info("✅ test find for exact path done")
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def test_find_with_array_input():
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img_path = os.path.join("dataset", "img1.jpg")
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img1 = cv2.imread(img_path)
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results = DeepFace.find(img1, db_path="dataset", silent=True, batched=True)
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assert len(results) > 0
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for result in results:
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assert isinstance(result, list)
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found_image_itself = False
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for face in result:
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assert isinstance(face, dict)
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if face["identity"] == img_path:
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# validate reproducability
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assert face["distance"] < threshold
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# one is img1.jpg itself
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found_image_itself = True
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assert found_image_itself
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assert len(results[0]) > 1
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logger.info("✅ test find for array input done")
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def test_find_with_extracted_faces():
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img_path = os.path.join("dataset", "img1.jpg")
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face_objs = DeepFace.extract_faces(img_path)
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img = face_objs[0]["face"]
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results = DeepFace.find(img, db_path="dataset", detector_backend="skip", silent=True, batched=True)
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assert len(results) > 0
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for result in results:
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assert isinstance(result, list)
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found_image_itself = False
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for face in result:
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assert isinstance(face, dict)
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if face["identity"] == img_path:
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# validate reproducability
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assert face["distance"] < threshold
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# one is img1.jpg itself
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found_image_itself = True
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assert found_image_itself
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assert len(results[0]) > 1
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logger.info("✅ test find for extracted face input done")
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def test_filetype_for_find():
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"""
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only images as jpg and png can be loaded into database
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"""
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img_path = os.path.join("dataset", "img1.jpg")
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results = DeepFace.find(img_path=img_path, db_path="dataset", silent=True, batched=True)
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result = results[0]
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assert not any(face["identity"] == "dataset/img47.jpg" for face in result)
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logger.info("✅ test wrong filetype done")
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