If you want to distill model in OpenMMLab related repos, please use MMRazor!!

If you are intrested in KD，you also could contact me by Wechat, and I will invite you to the KD group.

This project is based on mmdetection(v-2.9.0), all the usage is the same as mmdetection including training , test and so on.

Distiller Zoo

• [x] Channel-wise Distillation for Semantic Segmentation
• [ ] Improve Object Detection with Feature-based Knowledge Distillation: Towards Accurate and Efficient Detectors

Installation

• Set up a new conda environment: conda create -n distiller python=3.7

• Install pytorch

• Install mmcv ( 1.2.4 <= mmcv-full < 1.3 )

• Install mmdetection-distiller

  git clone https://github.com/pppppM/mmdetection-distiller.git
  cd mmdetection-distiller
  pip install -r requirements/build.txt
  pip install -v -e .
  

Train

#single GPU
python tools/train.py configs/distillers/cwd/cwd_retina_rx101_64x4d_distill_retina_r50_fpn_2x_coco.py

#multi GPU
bash tools/dist_train.sh configs/distillers/cwd/cwd_retina_rx101_64x4d_distill_retina_r50_fpn_2x_coco.py 8

Test

#single GPU
python tools/test.py configs/distillers/cwd/cwd_retina_rx101_64x4d_distill_retina_r50_fpn_2x_coco.py $CHECKPOINT --eval bbox

#multi GPU
bash tools/dist_train.sh configs/distillers/cwd/cwd_retina_rx101_64x4d_distill_retina_r50_fpn_2x_coco.py $CHECKPOINT 8 --eval bbox

Lisence

This project is released under the Apache 2.0 license.