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Objectness

BING Objectness proposal estimator linux/mac/windows version implementation, runs at 1000 FPS. This code is under BSD License. Objectness Proposal estimator运行代码,已经在linux/mac/windows下测试成功, 执行速度超过1000帧每秒。

This is the 1000 FPS BING objectness linux version library for efficient objectness proposal estimator following the CVPR 2014 paper BING, please consider to cite and refer to this paper.

@inproceedings{BingObj2014, title={{BING}: Binarized Normed Gradients for Objectness Estimation at 300fps}, author={Ming-Ming Cheng and Ziming Zhang and Wen-Yan Lin and Philip H. S. Torr}, booktitle={IEEE CVPR}, year={2014}, }

The original author Ming-Ming Cheng has already released the source code for windows 64-bit platform. In this library, we intend to release the code for the linux/mac/windows users. You can maintain the code with Qt Creator IDE.

Please find the original windows code / FAQ / Paper from this link: http://mmcheng.net/bing/

In order to make the code running as the original version in windows, you need to download the images/annotations PASCAL VOC 2007 data from the website. (http://pascallin.ecs.soton.ac.uk/challenges/VOC/voc2007/#testdata)

We have tested the code, it produces the same accuracy results as the original windows version, while it runs at 1111 FPS(frame per second) at Ubuntu 12.04 with a Dell T7600 workstation computer, which has two Intel Xeon E5-2687W (3.1GHz, 1600MHz) and 64 GB 1600MHz DDR3 Memory.

FAQ

  1. To run the code, you have to install OpenCV in the your ubuntu linux system. We specify the dependencies on opencv at " include_directories(/usr/local/include) link_directories(/usr/local/lib) "
  2. You can use/debug/change the code with Qt Creator IDE on ubuntu/mac.

Author: Ming-Ming Cheng(程明明) [email protected] Linux Author: Shuai Zheng (Kyle,郑帅) [email protected] Please find more information from http://kylezheng.org/objectness/ Date: 19, February

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