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Aladdin Persson
2021-01-30 21:49:15 +01:00
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ML/TensorFlow/CNN_architectures/VGGNet/test.py Normal file
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# disable tensorflow debugging messages
import os
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'
from vggnet import VGGNet
# Integer value represents output channel after performing the convolution layer
# 'M' represents the max pooling layer
# After convolution blocks; flatten the output and use 4096x4096x1000 Linear Layers
# with soft-max at the end
VGG_types = {
'VGG11': [64, 'M', 128, 'M', 256, 256, 'M', 512, 512, 'M', 512, 512, 'M'],
'VGG13': [64, 64, 'M', 128, 128, 'M', 256, 256, 'M', 512, 512, 'M', 512, 512, 'M'],
'VGG16': [64, 64, 'M', 128, 128, 'M', 256, 256, 256, 'M', 512, 512, 512, 'M', 512, 512, 512, 'M'],
'VGG19': [64, 64, 'M', 128, 128, 'M', 256, 256, 256, 256, 'M', 512, 512, 512, 512, 'M', 512, 512, 512, 512, 'M'],
}
if __name__ == "__main__":
# test VGGNet16
model = VGGNet(name = "VGGNet16", architecture = VGG_types["VGG16"], input_shape=(224, 224, 3), classes = 1000)
model.summary()