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https://github.com/iperov/DeepFaceLab.git
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64 lines
No EOL
2.3 KiB
Python
64 lines
No EOL
2.3 KiB
Python
from nnlib import nnlib
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def VGGFace():
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exec(nnlib.import_all(), locals(), globals())
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img_input = Input(shape=(224,224,3) )
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# Block 1
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x = Conv2D(64, (3, 3), activation='relu', padding='same', name='conv1_1')(
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img_input)
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x = Conv2D(64, (3, 3), activation='relu', padding='same', name='conv1_2')(x)
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x = MaxPooling2D((2, 2), strides=(2, 2), name='pool1')(x)
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# Block 2
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x = Conv2D(128, (3, 3), activation='relu', padding='same', name='conv2_1')(
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x)
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x = Conv2D(128, (3, 3), activation='relu', padding='same', name='conv2_2')(
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x)
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x = MaxPooling2D((2, 2), strides=(2, 2), name='pool2')(x)
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# Block 3
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x = Conv2D(256, (3, 3), activation='relu', padding='same', name='conv3_1')(
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x)
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x = Conv2D(256, (3, 3), activation='relu', padding='same', name='conv3_2')(
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x)
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x = Conv2D(256, (3, 3), activation='relu', padding='same', name='conv3_3')(
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x)
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x = MaxPooling2D((2, 2), strides=(2, 2), name='pool3')(x)
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# Block 4
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x = Conv2D(512, (3, 3), activation='relu', padding='same', name='conv4_1')(
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x)
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x = Conv2D(512, (3, 3), activation='relu', padding='same', name='conv4_2')(
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x)
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x = Conv2D(512, (3, 3), activation='relu', padding='same', name='conv4_3')(
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x)
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x = MaxPooling2D((2, 2), strides=(2, 2), name='pool4')(x)
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# Block 5
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x = Conv2D(512, (3, 3), activation='relu', padding='same', name='conv5_1')(
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x)
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x = Conv2D(512, (3, 3), activation='relu', padding='same', name='conv5_2')(
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x)
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x = Conv2D(512, (3, 3), activation='relu', padding='same', name='conv5_3')(
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x)
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x = MaxPooling2D((2, 2), strides=(2, 2), name='pool5')(x)
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# Classification block
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x = Flatten(name='flatten')(x)
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x = Dense(4096, name='fc6')(x)
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x = Activation('relu', name='fc6/relu')(x)
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x = Dense(4096, name='fc7')(x)
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x = Activation('relu', name='fc7/relu')(x)
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x = Dense(2622, name='fc8')(x)
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x = Activation('softmax', name='fc8/softmax')(x)
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model = Model(img_input, x, name='vggface_vgg16')
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weights_path = keras.utils.data_utils.get_file('rcmalli_vggface_tf_vgg16.h5',
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'https://github.com/rcmalli/keras-vggface/releases/download/v2.0/rcmalli_vggface_tf_vgg16.h5')
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model.load_weights(weights_path, by_name=True)
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return model |