mirror of
https://github.com/serengil/deepface.git
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57 lines
1.7 KiB
Python
57 lines
1.7 KiB
Python
import os
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from pathlib import Path
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import gdown
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import zipfile
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from tensorflow import keras
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from tensorflow.keras.models import Model
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from tensorflow.keras.layers import Conv2D, Activation, Input, Add, MaxPooling2D, Flatten, Dense, Dropout
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from deepface.commons import functions
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#-------------------------------------
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#url = 'https://drive.google.com/uc?id=1uRLtBCTQQAvHJ_KVrdbRJiCKxU8m5q2J'
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def loadModel(url = 'https://github.com/serengil/deepface_models/releases/download/v1.0/deepid_keras_weights.h5'):
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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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