82 lines
2.1 KiB
Python
82 lines
2.1 KiB
Python
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import os
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import gdown
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import tensorflow as tf
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from deepface.commons import functions
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tf_version = int(tf.__version__.split(".", maxsplit=1)[0])
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if tf_version == 1:
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from keras.models import Model
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from keras.layers import (
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Conv2D,
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Activation,
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Input,
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Add,
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MaxPooling2D,
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Flatten,
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Dense,
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Dropout,
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)
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else:
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from tensorflow.keras.models import Model
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from tensorflow.keras.layers import (
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Conv2D,
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Activation,
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Input,
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Add,
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MaxPooling2D,
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Flatten,
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Dense,
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Dropout,
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)
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# pylint: disable=line-too-long
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# -------------------------------------
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def loadModel(
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url="https://github.com/serengil/deepface_models/releases/download/v1.0/deepid_keras_weights.h5",
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):
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myInput = Input(shape=(55, 47, 3))
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x = Conv2D(20, (4, 4), name="Conv1", activation="relu", input_shape=(55, 47, 3))(myInput)
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x = MaxPooling2D(pool_size=2, strides=2, name="Pool1")(x)
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x = Dropout(rate=0.99, name="D1")(x)
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x = Conv2D(40, (3, 3), name="Conv2", activation="relu")(x)
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x = MaxPooling2D(pool_size=2, strides=2, name="Pool2")(x)
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x = Dropout(rate=0.99, name="D2")(x)
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x = Conv2D(60, (3, 3), name="Conv3", activation="relu")(x)
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x = MaxPooling2D(pool_size=2, strides=2, name="Pool3")(x)
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x = Dropout(rate=0.99, name="D3")(x)
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x1 = Flatten()(x)
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fc11 = Dense(160, name="fc11")(x1)
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x2 = Conv2D(80, (2, 2), name="Conv4", activation="relu")(x)
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x2 = Flatten()(x2)
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fc12 = Dense(160, name="fc12")(x2)
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y = Add()([fc11, fc12])
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y = Activation("relu", name="deepid")(y)
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model = Model(inputs=[myInput], outputs=y)
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# ---------------------------------
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home = functions.get_deepface_home()
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if os.path.isfile(home + "/.deepface/weights/deepid_keras_weights.h5") != True:
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print("deepid_keras_weights.h5 will be downloaded...")
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output = home + "/.deepface/weights/deepid_keras_weights.h5"
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gdown.download(url, output, quiet=False)
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model.load_weights(home + "/.deepface/weights/deepid_keras_weights.h5")
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return model
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