This project has moved to ChainerCV.
chainer-light-head-rcnn - Light Head RCNN
This is Chainer implementation of Light-Head R-CNN: In Defense of Two-Stage Object Detector.
Original TensorFlow repository is zengarden/light_head_rcnn.
Requirement
Additional Requirement
- For COCO Dataset class
- For training
Evaluation Score
| Implementation | mAP@0.5:0.95/all | mAP@0.5/all | mAP@0.75/all | mAP:0.5:0.95/small | mAP:0.5:0.95/medium | mAP:0.5:0.95/large |
|---|---|---|---|---|---|---|
| Original | 0.400 | 0.621 | 0.429 | 0.225 | 0.446 | 0.540 |
| Ours | 0.391 | 0.607 | 0.419 | 0.212 | 0.428 | 0.541 |
Installation
We recommend to use Anacoda.
# Requirement installation
conda create -n light-head-rcnn python=3.6
source activate light-head-rcnn
pip install opencv-python
pip install cupy
# Installation
git clone https://github.com/knorth55/chainer-light-head-rcnn.git
cd chainer-light-head-rcnn/
pip install -e .Inference
cd examples/
python demo.py <imagepath> --gpu <gpu>Training
cd examples/
mpiexec -n <n_gpu> python train_multi.py