It didn't perform any better than the regular model Removing batch normalisation significantly harmed training performance
12 lines
384 B
Python
12 lines
384 B
Python
import fast_depth_functional as fd
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if __name__ == '__main__':
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fd.fix_windows_gpu()
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model = fd.mobilenet_nnconv5(weights='imagenet')
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fd.compile(model)
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fd.train(existing_model=model, save_file='../fast-depth-experimental')
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fd.evaluate(model)
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# Save in Tensorflow SavedModel format
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# tf.saved_model.save(model, 'fast_depth_nyu_v2_224_224_3_e1_saved_model')
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