Design of a convolution neural networks for image feature extraction fast, and you can choose whether to use the GPU itself according to the environment

caffe-master
............\.gitignore
............\LICENSE
............\Makefile
............\Makefile.config
............\README.md
............\caffe.cloc
............\data
............\....\get_mnist.sh
............\....\lenet.prototxt
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............\....\lenet_test.prototxt
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............\examples
............\........\convert_cifar_data.cpp
............\........\convert_imageset.cpp
............\........\convert_mnist_data.cpp
............\........\demo_compute_image_mean.cpp
............\........\dump_network.cpp
............\........\finetune_net.cpp
............\........\imagenet.prototxt
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............\........\net_speed_benchmark.cpp
............\........\synset_words.txt
............\........\test_net.cpp
............\........\train_net.cpp
............\include
............\.......\caffe
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............\.......\.....\caffe.hpp
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............\matlab
............\......\caffe
............\......\.....\ilsvrc_2012_mean.mat
............\......\.....\matcaffe.cpp
............\......\.....\matcaffe_demo.m
............\python
............\......\caffe
............\......\.....\__init__.py
............\......\.....\convert.py
............\......\.....\drawnet.py
............\......\.....\imagenet
............\......\.....\........\__init__.py
............\......\.....\........\ilsvrc_2012_mean.npy
............\......\.....\........\ilsvrc_2012_synsets.txt
............\......\.....\........\ilsvrc_2012_test.txt
............\......\.....\........\ilsvrc_2012_train.txt
............\......\.....\........\ilsvrc_2012_val.txt
............\......\.....\........\power_wrapper.py
............\......\.....\........\selective_search_demo.ipynb
............\......\.....\........\wrapper.py
............\......\.....\proto
............\......\.....\.....\__init__.py
............\......\.....\pycaffe.cpp
............\src
............\...\caffe
............\...\.....\blob.cpp
............\...\.....\common.cpp
............\...\.....\layer_factory.cpp
............\...\.....\layers
............\...\.....\......\bnll_layer.cu
............\...\.....\......\conv_layer.cpp
............\...\.....\......\data_layer.cpp
............\...\.....\......\dropout_layer.cu
............\...\.....\......\flatten_layer.cpp
............\...\.....\......\im2col_layer.cpp
............\...\.....\......\inner_product_layer.cpp
............\...\.....\......\loss_layer.cu
............\...\.....\......\lrn_layer.cpp
............\...\.....\......\lrn_layer.cu
............\...\.....\......\neuron_layer.cpp
............\...\.....\......\padding_layer.cu
............\...\.....\......\pooling_layer.cpp
............\...\.....\......\pooling_layer.cu
............\...\.....\......\relu_layer.cu
............\...\.....\......\softmax_layer.cu
............\...\.....\......\softmax_loss_layer.cu
............\...\.....\net.cpp
............\...\.....\proto
............\...\.....\.....\caffe.proto
............\...\.....\solver.cpp
............\...\.....\syncedmem.cpp
............\...\.....\test
............\...\.....\....\test_blob.cpp
............\...\.....\....\test_caffe_main.hpp
............\...\.....\....\test_common.cpp
............\...\.....\....\test_convolution_layer.cpp
............\...\.....\....\test_data_layer.cpp

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