chainer-light-head-rcnn
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[This project has moved to ChainerCV] Chainer Implementation of Light Head RCNN
This project has moved to ChainerCV.
chainer-light-head-rcnn - Light Head RCNN
![](https://github.com/knorth55/chainer-light-head-rcnn/raw/master/static/coco_example.png)
![](https://github.com/knorth55/chainer-light-head-rcnn/raw/master/static/coco_example_1.png)
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 | [email protected]:0.95/all | [email protected]/all | [email protected]/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
LICENSE
MIT LICENSE