RPN+(Tensorflow) for people detection
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README.md

RPNplus

Code accompanying the paper "Expecting the Unexpected: Training Detectors for Unusual Pedestrians with Adversarial Imposters(CVPR2017)". As for the generator for synthetic data, please take this repo for reference.

Requirement

  • ubuntu or Mac OS
  • tensorflow==1.1+
  • pip install image
  • pip install sklearn
  • pip install scipy
  • image_pylib(This repository should be put under the same folder with RPNplus.)

Usage

Run Demo:

  • Download model files(RPN_model & VGG16_model) first, and put them in the ./models/ folder.
  • The number 0 is your GPU index, and you can change to any available GPU index.
  • This demo will test the images in the ./images/ folder and output the results to ./results/ folder.
python demo.py 0

ATOCAR Logo

Train:

  • The number 0 is your GPU index, and you can change to any available GPU index.
  • Open train.py and set imageLoadDir and anoLoadDir to proper values(imageLoadDir means where you store your images and anoLoadDir means where you store your annotation files).
python train.py 0

Dataset Download

Related Datasets

Cite

Please cite our paper if you use this code or our datasets in your own work:

@InProceedings{Huang_2017_CVPR,
author = {Huang, Shiyu and Ramanan, Deva},
title = {Expecting the Unexpected: Training Detectors for Unusual Pedestrians With Adversarial Imposters},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {July},
year = {2017}
}

Acknowledgement

Author

Shiyu Huang(huangsy13@gmail.com)