yangkang779 / CSP-pedestrian-detection-in-pytorch

Unofficially Pytorch implementation of High-level Semantic Feature Detection: A New Perspective for Pedestrian Detection

CSP PyTorch Implementation

Unofficially Pytorch implementation of High-level Semantic Feature Detection: A New Perspective for Pedestrian Detection

This code is only for CityPersons dataset, and only for center-position+height regression+offset regression model.

NOTE

This repo's codes have bugs, and will not be updated for days or weeks. you may run the code, but check it carefully. A new repo may be uploaded in the future.

update

On Cityperson validation set 11.70 MR BaiduYun https://pan.baidu.com/s/1t5JhFvFM0Z8xObmqva0Gtg password:xarm

11.71 MR CSPNet-26.pth (NEW !)

12.56 MR CSPNet-89.pth

Requirement

Python, pytorch and other related libaries

GPU is needed

Usage

Compile lib

cd util
make all

Prepare CityPersons dataset as the original codes doing

• For citypersons, we use the training set (2975 images) for training and test on the validation set (500 images), we assume that images and annotations are stored in ./data/citypersons, and the directory structure is

*DATA_PATH
	*annotations
		*anno_train.mat
		*anno_val.mat
	*images
		*train
		*val

Training & val

python trainval_torchstyle.py
python trainval_caffestyle.py

NOTE

using caffe style, you need to download additional pre-trained weight.