Awesome
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.