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dmitrygolovkindmitrygolovkin
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Update models. Add new compressed, pruned and random-pruned for many models
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‎caffe_models/denoiser/caffe_model/Compressed_Denoiser_1_5x_80-36.caffemodel‎

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‎caffe_models/denoiser/caffe_model/Compressed_Denoiser_SSIM_drop_zero_1-76x_80-30.caffemodel‎

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‎caffe_models/denoiser/caffe_model/net-HxW-64-64_iter_970_random_pruned.caffemodel‎

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‎caffe_models/denoiser/caffe_model/notes.txt‎

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--image_scale 1
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to run denoiser. The graph is trained assuming the input pixels
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are in the range [0..1].
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Compressed + Pruned:
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1. PROTOTXT??? and Compressed_Denoiser_1_5x_80-36.caffemodel (factor 1.5)
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2. PROTOTXT??? and Compressed_Denoiser_SSIM_drop_zero_1-76x_80-30.caffemodel (factor 1.76)
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3. net-200x200-64-64-test.prototxt / net-240x360-64-64-test.prototxt and net-HxW-64-64_iter_970_random_pruned.caffemodel (random pruned 60%/85%)
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‎caffe_models/densenet/caffe_model/121/DenseNet_121_random_pruned.caffemodel‎

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‎caffe_models/densenet/caffe_model/161/DenseNet_161_random_pruned.caffemodel‎

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‎caffe_models/densenet/caffe_model/169/DenseNet_169_random_pruned.caffemodel‎

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‎caffe_models/densenet/caffe_model/201/DenseNet_201_random_pruned.caffemodel‎

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‎caffe_models/densenet/notes.txt‎

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ceil_mode: false is used in the first pooling layers ('pool1')
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Pruned Graphs
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1. DenseNet_*.prototxt / DenseNet_*_random_pruned.caffemodel
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- random pruned (conv: 60%, fc: 85%)

‎caffe_models/facedetect_v1/caffe_model/face_random_pruned.caffemodel‎

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