代码拉取完成,页面将自动刷新
git clone https://github.com/luanshiyinyang/ExpressionRecognition.git
cd ExpressionRecognition
pip install -r requirements.txt
def CNN3(input_shape=(48, 48, 1), n_classes=8):
"""
参考论文实现
A Compact Deep Learning Model for Robust Facial Expression Recognition
:param input_shape:
:param n_classes:
:return:
"""
# input
input_layer = Input(shape=input_shape)
x = Conv2D(32, (1, 1), strides=1, padding='same', activation='relu')(input_layer)
# block1
x = Conv2D(64, (3, 3), strides=1, padding='same')(x)
x = PReLU()(x)
x = Conv2D(64, (5, 5), strides=1, padding='same')(x)
x = PReLU()(x)
x = MaxPooling2D(pool_size=(2, 2), strides=2)(x)
# block2
x = Conv2D(64, (3, 3), strides=1, padding='same')(x)
x = PReLU()(x)
x = Conv2D(64, (5, 5), strides=1, padding='same')(x)
x = PReLU()(x)
x = MaxPooling2D(pool_size=(2, 2), strides=2)(x)
# fc
x = Flatten()(x)
x = Dense(2048, activation='relu')(x)
x = Dropout(0.5)(x)
x = Dense(1024, activation='relu')(x)
x = Dropout(0.5)(x)
x = Dense(n_classes, activation='softmax')(x)
model = Model(inputs=input_layer, outputs=x)
return model
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