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vgg-caffe's Introduction

VGG16 and VGG19 caffe net

Uses the VGG16 and VGG19 nets from the modelzoo. Minor changes in the *.prototxt to adapt it to the new caffe version.

See net.ipynb.

Instructions

# Download models 
wget --show-progress -P 'model/' 'http://www.robots.ox.ac.uk/~vgg/software/very_deep/caffe/VGG_ILSVRC_16_layers.caffemodel'
wget --show-progress -P 'model/' 'http://www.robots.ox.ac.uk/~vgg/software/very_deep/caffe/VGG_ILSVRC_19_layers.caffemodel'

# Convert models to new caffe format (caffe needed)
# (Not strictly needed. Removes deprecation notice)
upgrade_net_proto_binary MODEL.caffemodel MODEL.new.caffemodel

# Build docker image
docker build docker/ -t caffe-jupyter

# Start jupyter notebook
./docker/start-jupyter.sh

# Open browser at 127.0.0.1:8888
# Enter 'a' as the password to enter the jupyter env

# Maybe you have to adapt some paths to the models. See net.ipynb

# Docker terminal to image to execute "upgrade_net_proto_binary" etc. and run python files normally
docker run --entrypoint  --rm -v $(pwd):$(pwd) -w $(pwd) -it caffe-jupyter bash

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vgg-caffe's Issues

Memory problem with vgg networks

Hi,
I have a laptop computer with GeForce 755 M (2 gb ram). I can successfully train and test googlenet and alexnet using nvidia digits on Ubuntu 16.04, and caffe. But when I use prototxt's of these vgg16 and vgg19 using the same data, I immdeiately get memory allocation error. I want to learn if my laptop is too weak to handle those networks. I am keeping batch size very low like 3, 2, and even 1. Is there anything to do it with my existing computer (need to use gpu support, since without it training will last a week at least)?

I desperately need help for it.
Thanks in advance!

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