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[update] modify test of emotion
and add client of age
, gender
and race
tests
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@ -4,6 +4,7 @@ import numpy as np
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# project dependencies
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from deepface import DeepFace
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from deepface.models.demography import Age, Emotion, Gender, Race
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from deepface.commons.logger import Logger
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logger = Logger()
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@ -150,11 +151,46 @@ def test_analyze_for_multiple_faces_in_one_image():
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assert demography["dominant_gender"] == "Woman"
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logger.info("✅ test analyze for multiple faces in one image done")
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def test_batch_detect_emotion_for_multiple_faces():
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img = "dataset/img4.jpg"
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img = cv2.imread(img)
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def test_batch_detect_age_for_multiple_faces():
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# Load test image and resize to model input size
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img = cv2.resize(cv2.imread("dataset/img1.jpg"), (224, 224))
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imgs = [img, img]
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results = DeepFace.demography.Emotion.EmotionClient().predict(imgs)
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results = Age.ApparentAgeClient().predict(imgs)
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# Check there are two ages detected
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assert len(results) == 2
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# Check two faces ages are the same
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assert np.array_equal(results[0], results[1])
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logger.info("✅ test batch detect age for multiple faces done")
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def test_batch_detect_emotion_for_multiple_faces():
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# Load test image and resize to model input size
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img = cv2.resize(cv2.imread("dataset/img1.jpg"), (224, 224))
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imgs = [img, img]
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results = Emotion.EmotionClient().predict(imgs)
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# Check there are two emotions detected
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assert len(results) == 2
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# Check two faces emotions are the same
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assert np.array_equal(results[0], results[1])
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logger.info("✅ test batch detect emotion for multiple faces done")
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def test_batch_detect_gender_for_multiple_faces():
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# Load test image and resize to model input size
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img = cv2.resize(cv2.imread("dataset/img1.jpg"), (224, 224))
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imgs = [img, img]
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results = Gender.GenderClient().predict(imgs)
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# Check there are two genders detected
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assert len(results) == 2
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# Check two genders are the same
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assert np.array_equal(results[0], results[1])
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logger.info("✅ test batch detect gender for multiple faces done")
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def test_batch_detect_race_for_multiple_faces():
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# Load test image and resize to model input size
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img = cv2.resize(cv2.imread("dataset/img1.jpg"), (224, 224))
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imgs = [img, img]
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results = Race.RaceClient().predict(imgs)
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# Check there are two races detected
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assert len(results) == 2
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# Check two races are the same
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assert np.array_equal(results[0], results[1])
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logger.info("✅ test batch detect race for multiple faces done")
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