CNN_VGG19_CUDA
Convolutional Neural Network of VGG19 model using CUDA to accelerate
CNN architecture
VGG19 (imagenet-very-deep-vgg19.mat) - pretrained model by imagenet with 19 layers
Compile
make
Execution
./cnn_vgg19_cuda <image file in .txt> vgg19_weight.txt vgg19_bias.txt vgg19_output_1000.txt
Some useful tools
tools written by myself that will help a lot
vgg19.py
analyze imagenet-very-deep-vgg19.mat(need to download by yourself) and output to vgg19_weight/bias.txt
make vgg
image_converter.py
convert RGB value of .jpg(224 * 224) into .txt (in RGB order)
make image
softmax.py
convert output of the model, vgg19_output.txt, into problilities of
1000 classes corresponding to synset_word.txt and write to
vgg19_probs.txt
make softmax
image folder
contain some .jpg files and its corresponding .txt and predict files
p.s it's not actually a trainable model, just a reconstruction of vgg19 in evaluation phase