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import pytest
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import numpy as np
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from deepface import DeepFace
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from deepface.commons.logger import Logger
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logger = Logger()
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def test_enabled_enforce_detection_for_non_facial_input():
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black_img = np.zeros([224, 224, 3])
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with pytest.raises(ValueError):
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DeepFace.represent(img_path=black_img)
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with pytest.raises(ValueError):
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DeepFace.verify(img1_path=black_img, img2_path=black_img)
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logger.info("β
enabled enforce detection with non facial input tests done")
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def test_disabled_enforce_detection_for_non_facial_input_on_represent():
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black_img = np.zeros([224, 224, 3])
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objs = DeepFace.represent(img_path=black_img, enforce_detection=False)
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assert isinstance(objs, list)
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assert len(objs) > 0
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assert isinstance(objs[0], dict)
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assert "embedding" in objs[0].keys()
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assert "facial_area" in objs[0].keys()
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assert isinstance(objs[0]["facial_area"], dict)
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assert "x" in objs[0]["facial_area"].keys()
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assert "y" in objs[0]["facial_area"].keys()
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assert "w" in objs[0]["facial_area"].keys()
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assert "h" in objs[0]["facial_area"].keys()
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assert isinstance(objs[0]["embedding"], list)
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assert len(objs[0]["embedding"]) == 4096
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logger.info("β
disabled enforce detection with non facial input test for represent tests done")
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def test_disabled_enforce_detection_for_non_facial_input_on_verify():
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black_img = np.zeros([224, 224, 3])
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obj = DeepFace.verify(img1_path=black_img, img2_path=black_img, enforce_detection=False)
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assert isinstance(obj, dict)
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logger.info("β
disabled enforce detection with non facial input test for verify tests done")
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