Skip to content

huangshiyu13/RPNplus

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

37 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

RPNplus

This repository is not going to be updated anymore. The new detection model will be published here: TARTDetection

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([email protected])

Releases

No releases published

Packages

No packages published

Languages