This directory holds (after you download them):
- Caffe models pre-trained on ImageNet
- Faster R-CNN models
- Symlinks to datasets
To download Caffe models (ZF, VGG16) pre-trained on ImageNet, run:
./data/scripts/fetch_imagenet_models.sh
This script will populate data/imagenet_models.
To download Faster R-CNN models trained on VOC 2007, run:
./data/scripts/fetch_faster_rcnn_models.sh
This script will populate data/faster_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/er 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
# (only applicable to Fast R-CNN training)
ln -s /data/fast_rcnn_shared/selective_search_data
ln -s /data/VOC2007/VOCdevkit VOCdevkit2007
ln -s /data/VOC2012/VOCdevkit VOCdevkit2012