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andreaskoepf
124 Stars 54 Forks MIT License 26 Commits 6 Opened issues

Description

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

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faster-rcnn

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.

Todo:

  • [!] 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

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