更换文档检测模型

2024-08-27 14:42:45 +08:00
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+English | [简体中文](README_cn.md)
+
+# SNIPER: Efficient Multi-Scale Training
+
+## Model Zoo
+
+| Sniper   | GPU number    | images/GPU |    Model  |    Dataset     | Schedulers | Box AP |          Download                  | Config |
+| :---------------- | :-------------------: | :------------------: | :-----: | :-----: | :------------: | :-----: | :-----------------------------------------------------: | :-----: |
+| w/o   |    4    |    1    | ResNet-r50-FPN      | [VisDrone](https://github.com/VisDrone/VisDrone-Dataset)  |   1x    |  23.3  | [Download Link](https://bj.bcebos.com/v1/paddledet/models/faster_rcnn_r50_fpn_1x_visdrone.pdparams ) | [config](./faster_rcnn_r50_fpn_1x_visdrone.yml) |
+| w/ |    4    |    1    | ResNet-r50-FPN      | [VisDrone](https://github.com/VisDrone/VisDrone-Dataset)   |   1x    |  29.7  | [Download Link](https://bj.bcebos.com/v1/paddledet/models/faster_rcnn_r50_fpn_1x_sniper_visdrone.pdparams) | [config](./faster_rcnn_r50_fpn_1x_sniper_visdrone.yml) |
+
+### Note
+- Here, we use VisDrone dataset, and to detect 9 objects including `person, bicycles, car, van, truck, tricycle, awning-tricycle, bus, motor`.
+- Do not support deploy by now because sniper dataset crop behavior.
+
+## Getting Start
+### 1. Training
+a. optional: Run `tools/sniper_params_stats.py` to get image_target_sizes\valid_box_ratio_ranges\chip_target_size\chip_target_stride，and modify this params in configs/datasets/sniper_coco_detection.yml
+```bash
+python tools/sniper_params_stats.py FasterRCNN annotations/instances_train2017.json
+```
+b. optional: train detector to get negative proposals.
+```bash
+python -m paddle.distributed.launch --log_dir=./sniper/ --gpus 0,1,2,3,4,5,6,7 tools/train.py -c configs/sniper/faster_rcnn_r50_fpn_1x_sniper_visdrone.yml --save_proposals --proposals_path=./proposals.json &>sniper.log 2>&1 &
+```
+c. train models
+```bash
+python -m paddle.distributed.launch --log_dir=./sniper/ --gpus 0,1,2,3,4,5,6,7 tools/train.py -c configs/sniper/faster_rcnn_r50_fpn_1x_sniper_visdrone.yml --eval &>sniper.log 2>&1 &
+```
+
+### 2. Evaluation
+Evaluating SNIPER on custom dataset in single GPU with following commands:
+```bash
+# use saved checkpoint in training
+CUDA_VISIBLE_DEVICES=0 python tools/eval.py -c configs/sniper/faster_rcnn_r50_fpn_1x_sniper_visdrone.yml -o weights=output/faster_rcnn_r50_fpn_1x_sniper_visdrone/model_final
+```
+
+### 3. Inference
+Inference images in single GPU with following commands, use `--infer_img` to inference a single image and `--infer_dir` to inference all images in the directory.
+
+```bash
+# inference single image
+CUDA_VISIBLE_DEVICES=0 python tools/infer.py -c configs/sniper/faster_rcnn_r50_fpn_1x_sniper_visdrone.yml -o weights=output/faster_rcnn_r50_fpn_1x_sniper_visdrone/model_final --infer_img=demo/P0861__1.0__1154___824.png
+
+# inference all images in the directory
+CUDA_VISIBLE_DEVICES=0 python tools/infer.py -c configs/sniper/faster_rcnn_r50_fpn_1x_sniper_visdrone.yml -o weights=output/faster_rcnn_r50_fpn_1x_sniper_visdrone/model_final --infer_dir=demo
+```
+
+## Citations
+```
+@misc{1805.09300,
+Author = {Bharat Singh and Mahyar Najibi and Larry S. Davis},
+Title = {SNIPER: Efficient Multi-Scale Training},
+Year = {2018},
+Eprint = {arXiv:1805.09300},
+}
+
+@ARTICLE{9573394,
+  author={Zhu, Pengfei and Wen, Longyin and Du, Dawei and Bian, Xiao and Fan, Heng and Hu, Qinghua and Ling, Haibin},
+  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
+  title={Detection and Tracking Meet Drones Challenge},
+  year={2021},
+  volume={},
+  number={},
+  pages={1-1},
+  doi={10.1109/TPAMI.2021.3119563}}
+```