The reconstruction implementation of PRM by removing third-party dependency(i.e, Nest).

Motivation: An ultra-thin version of PRM, which aims at improving readability and expansibility.

Rule No.1: Never make code too complicated. 😂

Version info: pytorch 0.4.1, python 3.6

Training & Inference

Training:

python main.py --train True

Inference:

python main.py 

Sample result

Reference

@INPROCEEDINGS{Zhou2018PRM,
    author = {Zhou, Yanzhao and Zhu, Yi and Ye, Qixiang and Qiu, Qiang and Jiao, Jianbin},
    title = {Weakly Supervised Instance Segmentation using Class Peak Response},
    booktitle = {CVPR},
    year = {2018}
}