Ewenwan/ristretto_ssd

ristretto 量化ssd

Installation

1. Get the code. We will call the directory that you cloned Caffe into $CAFFE_ROOT

https://github.com/chaitu2289/ristretto_ssd
cd ristretto_ssd

2. Build the code. Please follow Caffe instruction to install all necessary packages and build it.

# Modify Makefile.config according to your Caffe installation.
cp Makefile.config.example Makefile.config
make -j8
# Make sure to include $CAFFE_ROOT/python to your PYTHONPATH.
make py
make test -j8
make runtest -j8
# If you have multiple GPUs installed in your machine, make runtest might fail. If so, try following:
export CUDA_VISIBLE_DEVICES=0; make runtest -j8
# If you have error: "Check failed: error == cudaSuccess (10 vs. 0)  invalid device ordinal",
# first make sure you have the specified GPUs, or try following if you have multiple GPUs:
unset CUDA_VISIBLE_DEVICES

Preparation

1. Download trained PASCAL VOC models(07 + 12).

   cd $HOME
   tar -zxvf models_VGGNet_VOC0712_SSD_300x300.tar.gz

   This will create the following files

   models/VGGNet/VOC0712/SSD_300x300/
   models/VGGNet/VOC0712/SSD_300x300/test.prototxt
   models/VGGNet/VOC0712/SSD_300x300/deploy.prototxt
   models/VGGNet/VOC0712/SSD_300x300/VGG_VOC0712_SSD_300x300_iter_120000.caffemodel
   models/VGGNet/VOC0712/SSD_300x300/solver.prototxt
   models/VGGNet/VOC0712/SSD_300x300/train.prototxt
   models/VGGNet/VOC0712/SSD_300x300/ssd_pascal.py
   models/VGGNet/VOC0712/SSD_300x300/score_ssd_pascal.py

2. Download VOC2007 and VOC2012 dataset. By default, we assume the data is stored in $HOME/data/

# Download the data.
cd $HOME/data
wget http://host.robots.ox.ac.uk/pascal/VOC/voc2012/VOCtrainval_11-May-2012.tar
wget http://host.robots.ox.ac.uk/pascal/VOC/voc2007/VOCtrainval_06-Nov-2007.tar
wget http://host.robots.ox.ac.uk/pascal/VOC/voc2007/VOCtest_06-Nov-2007.tar
# Extract the data.
tar -xvf VOCtrainval_11-May-2012.tar
tar -xvf VOCtrainval_06-Nov-2007.tar
tar -xvf VOCtest_06-Nov-2007.tar

3. Create the LMDB file.

cd $CAFFE_ROOT
# Create the trainval.txt, test.txt, and test_name_size.txt in data/VOC0712/
./data/VOC0712/create_list.sh
# You can modify the parameters in create_data.sh if needed.
# It will create lmdb files for trainval and test with encoded original image:
#   - $HOME/data/VOCdevkit/VOC0712/lmdb/VOC0712_trainval_lmdb
#   - $HOME/data/VOCdevkit/VOC0712/lmdb/VOC0712_test_lmdb
# and make soft links at examples/VOC0712/
./data/VOC0712/create_data.sh

4. Create a directory ssd in $CAFFE_ROOT/models

   cd $CAFFE_ROOT
   mkdir models/ssd

5. Run the following command to create the fixed point version of the ssd model

   ./examples/ssd/00_quantize_ssdnet.sh

License and Citation

Caffe is released under the BSD 2-Clause license. The BVLC reference models are released for unrestricted use.

Please cite Caffe in your publications if it helps your research:

@article{jia2014caffe,
  Author = {Jia, Yangqing and Shelhamer, Evan and Donahue, Jeff and Karayev, Sergey and Long, Jonathan and Girshick, Ross and Guadarrama, Sergio and Darrell, Trevor},
  Journal = {arXiv preprint arXiv:1408.5093},
  Title = {Caffe: Convolutional Architecture for Fast Feature Embedding},
  Year = {2014}
}