Need help with faster-rcnn.torch?
Click the “chat” button below for chat support from the developer who created it, or find similar developers for support.

About the developer

122 Stars 53 Forks MIT License 26 Commits 6 Opened issues


Experimental Torch7 implementation of RCNN for Object Detection with a Region Proposal Network

Services available


Need anything else?

Contributors list

# 167,101
25 commits


This is an experimental Torch7 implementation of Faster RCNN - a convnet for object detection with a region proposal network. For details about R-CNN please refer to the paper Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks by Shaoqing Ren, Kaiming He, Ross Girshick, Jian Sun.

Work in progress

Status: Basic detection in my personal environment works. A 'small' network is used that can be trained on a 4 GB GPU with 800x450 images. Began experimenting with ImageNet: create-imagenet-traindat.lua can be used to create a training data file for the ILSVRC2015 dataset.


  • [!] regularly evaluate net during traning to compute test-set loss
  • generate training graph with gnuplot
  • add final per class non-maximum suppression to generate final proposals (already included but eval code rewrite still pending)
  • remove hard coded path, create full set of command line options
  • add parameters to separately enable/disable training of bounding box proposal-network and fine-tuning + classification.

Experiments to run:

  • test smaller networks
  • 6x6 vs. 7x7 classification ROI-pooling output size
  • impact of RGB, YUV, Lab color space
  • test relevance of local contrast normalization

References / Review / Useful Links

We use cookies. If you continue to browse the site, you agree to the use of cookies. For more information on our use of cookies please see our Privacy Policy.