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batch run support added for facial attribute models #1298

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merged 1 commit into from
Aug 4, 2024
Merged

batch run support added for facial attribute models #1298

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4 changes: 3 additions & 1 deletion deepface/extendedmodels/Age.py
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Original file line number Diff line number Diff line change
Expand Up @@ -33,7 +33,9 @@ def __init__(self):
self.model_name = "Age"

def predict(self, img: np.ndarray) -> np.float64:
age_predictions = self.model.predict(img, verbose=0)[0, :]
# model.predict causes memory issue when it is called in a for loop
# age_predictions = self.model.predict(img, verbose=0)[0, :]
age_predictions = self.model(img, training=False).numpy()[0, :]
return find_apparent_age(age_predictions)


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5 changes: 4 additions & 1 deletion deepface/extendedmodels/Emotion.py
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Original file line number Diff line number Diff line change
Expand Up @@ -52,7 +52,10 @@ def predict(self, img: np.ndarray) -> np.ndarray:
img_gray = cv2.resize(img_gray, (48, 48))
img_gray = np.expand_dims(img_gray, axis=0)

emotion_predictions = self.model.predict(img_gray, verbose=0)[0, :]
# model.predict causes memory issue when it is called in a for loop
# emotion_predictions = self.model.predict(img_gray, verbose=0)[0, :]
emotion_predictions = self.model(img_gray, training=False).numpy()[0, :]

return emotion_predictions


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4 changes: 3 additions & 1 deletion deepface/extendedmodels/Gender.py
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Original file line number Diff line number Diff line change
Expand Up @@ -41,7 +41,9 @@ def __init__(self):
self.model_name = "Gender"

def predict(self, img: np.ndarray) -> np.ndarray:
return self.model.predict(img, verbose=0)[0, :]
# model.predict causes memory issue when it is called in a for loop
# return self.model.predict(img, verbose=0)[0, :]
return self.model(img, training=False).numpy()[0, :]


def load_model(
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4 changes: 3 additions & 1 deletion deepface/extendedmodels/Race.py
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Original file line number Diff line number Diff line change
Expand Up @@ -40,7 +40,9 @@ def __init__(self):
self.model_name = "Race"

def predict(self, img: np.ndarray) -> np.ndarray:
return self.model.predict(img, verbose=0)[0, :]
# model.predict causes memory issue when it is called in a for loop
# return self.model.predict(img, verbose=0)[0, :]
return self.model(img, training=False).numpy()[0, :]


def load_model(
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