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enforce tf 2.12 or less
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@ -23,7 +23,6 @@ if tf_major == 1:
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Flatten,
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Flatten,
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Dense,
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Dense,
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Dropout,
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Dropout,
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LocallyConnected2D,
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)
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)
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else:
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else:
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from tensorflow.keras.models import Model, Sequential
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from tensorflow.keras.models import Model, Sequential
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@ -33,7 +32,6 @@ else:
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Flatten,
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Flatten,
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Dense,
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Dense,
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Dropout,
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Dropout,
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LocallyConnected2D,
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)
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)
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@ -45,6 +43,14 @@ class DeepFaceClient(FacialRecognition):
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"""
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"""
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def __init__(self):
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def __init__(self):
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# DeepFace requires tf 2.12 or less
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if tf_major == 2 and tf_minor > 12:
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# Ref: https://github.com/serengil/deepface/pull/1079
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raise ValueError(
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"DeepFace model requires LocallyConnected2D but it is no longer supported"
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f" after tf 2.12 but you have {tf_major}.{tf_minor}. You need to downgrade your tf."
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)
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self.model = load_model()
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self.model = load_model()
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self.model_name = "DeepFace"
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self.model_name = "DeepFace"
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self.input_shape = (152, 152)
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self.input_shape = (152, 152)
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@ -69,6 +75,13 @@ def load_model(
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"""
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"""
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Construct DeepFace model, download its weights and load
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Construct DeepFace model, download its weights and load
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"""
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"""
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# we have some checks for this dependency in the init of client
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# putting this in global causes library initialization
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if tf_major == 1:
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from keras.layers import LocallyConnected2D
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else:
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from tensorflow.keras.layers import LocallyConnected2D
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base_model = Sequential()
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base_model = Sequential()
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base_model.add(
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base_model.add(
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Convolution2D(32, (11, 11), activation="relu", name="C1", input_shape=(152, 152, 3))
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Convolution2D(32, (11, 11), activation="relu", name="C1", input_shape=(152, 152, 3))
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