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README.md

This directory holds (after you download them):

  • Pre-computed object proposals
  • Caffe models pre-trained on ImageNet
  • Fast R-CNN models
  • Symlinks to datasets

To download precomputed Selective Search proposals for PASCAL VOC 2007 and 2012, run:

./data/scripts/fetch_selective_search_data.sh

This script will populate data/selective_search_data.

To download Caffe models (CaffeNet, VGG_CNN_M_1024, VGG16) pre-trained on ImageNet, run:

./data/scripts/fetch_imagenet_models.sh

This script will populate data/imagenet_models.

To download Fast R-CNN models trained on VOC 2007, run:

./data/scripts/fetch_fast_rcnn_models.sh

This script will populate data/fast_rcnn_models.

In order to train and test with PASCAL VOC, you will need to establish symlinks. From the data directory (cd data):

# For VOC 2007
ln -s /your/path/to/VOC2007/VOCdevkit VOCdevkit2007

# For VOC 2012
ln -s /your/path/to/VOC2012/VOCdevkit VOCdevkit2012

Since you'll likely be experimenting with multiple installs of Fast R-CNN in parallel, you'll probably want to keep all of this data in a shared place and use symlinks. On my system I create the following symlinks inside data:

# data/cache holds various outputs created by the datasets package
ln -s /data/fast_rcnn_shared/cache

# move the imagenet_models to shared location and symlink to them
ln -s /data/fast_rcnn_shared/imagenet_models

# move the selective search data to a shared location and symlink to them
ln -s /data/fast_rcnn_shared/selective_search_data

ln -s /data/VOC2007/VOCdevkit VOCdevkit2007
ln -s /data/VOC2012/VOCdevkit VOCdevkit2012