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-# FreeKD
-Official implementation of paper "FreeKD: Knowledge Distillation via Semantic Frequency Prompt", CVPR 2024.
+# FreeKD: Knowledge Distillation via Semantic Frequency Prompt
+
+:fire: Official implementation of paper "FreeKD: Knowledge Distillation via Semantic Frequency Prompt", CVPR 2024.
+
+By Yuan Zhang, Tao Huang, Jiaming Liu, Tao Jiang, Kuan Cheng, Shanghang Zhang
+
+<p align='center'>
+<img src='./assests/arch.png' alt='mask' width='700px'>
+</p>
+
+## Installation  
+
+### Install MMRazor 0.x
+
+```shell
+git clone -b 0.x https://github.com/open-mmlab/mmrazor.git
+cd mmrazor
+```
+
+```shell
+pip install -v -e .
+```
+
+### Prepare Data Set
+
+Download on [https://opendatalab.com](https://opendatalab.com)
+
+> [!Note]
+> If you want to distill on detection and segmentation, you should install mmdetection and mmsegmentation, respectively.
+
+## Reproducing our results
+
+### Train students with FreeKD
+
+This repo uses [MMRazor](https://github.com/open-mmlab/mmrazor) as the knowledge distillation toolkit. For environment setup, please see [docs/en/get_started.md](docs/en/get_started.md).
+
+**Train student:**  
+
+```shell
+cd mmrazor
+sh tools/mmdet/dist_train_mmdet.sh ${CONFIG} 8 ${WORK_DIR}
+```
+
+Example for reproducing our `reppoints_x101-reppoints-r50_coco` result:
+
+```shell
+sh tools/mmdet/dist_train_mmdet.sh freekd_reppoints_x101-reppoints-r50_coco.py 8 work_dirs/freekd_rep_x101-fpn_x50
+```
+
+
+### Results  
+
+* Baseline settings:  
+
+  |        Student         |         Teacher         | FreeKD |
+  | :--------------------: | :---------------------: | :------: |
+  | Faster RCNN-R50 (38.4) | Faster RCNN-R101 (39.8) |   40.8   |
+  |  RetinaNet-R50 (37.4)  |  RetinaNet-R101 (38.9)  |   39.9   |
+  |    FCOS-R50 (38.5)     |    FCOS-R101 (40.8)     |   42.9   |
+
+* Stronger teachers:
+
+  |        Student         |            Teacher            | FreeKD |
+  | :--------------------: | :---------------------------: | :------: |
+  | Faster RCNN-R50 (38.4) | Cascade Mask RCNN-X101 (45.6) |   42.4   |
+  |  RetinaNet-R50 (37.4)  |     RetinaNet-X101 (41.0)     |   41.0   |
+  |  RepPoints-R50 (38.6)  |     RepPoints-R101 (44.2)     |   42.4   |
+
+### Visualization
+
+<p align='center'>
+<img src='./assests/media.png' alt='mask' width='320px'>
+</p>
+
+## License  
+
+This project is released under the [Apache 2.0 license](LICENSE).
+
+## Citation  
+If you use FreeKD in your research, please cite our work by using the following BibTeX entry:
+```
+@article{zhang2023freekd,
+  title={FreeKD: Knowledge Distillation via Semantic Frequency Prompt},
+  author={Zhang, Yuan and Huang, Tao and Liu, Jiaming and Jiang, Tao and Cheng, Kuan and Zhang, Shanghang},
+  journal={arXiv preprint arXiv:2311.12079},
+  year={2023}
+}
+```
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