MMDetection中的操作

1. 训练

python tools/train.py [configs_file] --gpus 1 --work_dir work_dirs

2. 测试

（1）Output pkl file

​ This command will output “results_name.pkl” file.

python tools/test.py [configs_file] [pth] --out results_name.pkl --eval bbox

python tools/test.py configs/faster_rcnn/faster_rcnn_r50_fpn_1x_coco.py checkpoints/faster_rcnn_r50_fpn_1x_coco_20200130-047c8118.pth --out=work_dirs/result.pkl --eval bbox

（2） Output json result file

​ This command will output “results.bbox.json” file.

python tools/test.py [configs_file] [pth] --eval-options "jsonfile_prefix=results_name" --eval bbox

python tools/test.py configs/faster_rcnn/faster_rcnn_r50_fpn_1x_coco.py checkpoints/faster_rcnn_r50_fpn_1x_coco_20200130-047c8118.pth --eval bbox --eval-options "jsonfile_prefix=results"

3. 输出coco metric

python tools/analysis_tools/eval_metric.py [configs_file] [pkl_file] --eval bbox

python tools/analysis_tools/eval_metric.py configs/faster_rcnn/faster_rcnn_r50_fpn_1x_coco.py work_dirs/faster_rcnn_coco_result.pkl --eval bbox

4. 绘制PR曲线

python plot_pr_curve.py

5. Log Analysis

python tools/analysis_tools/analyze_logs.py plot_curve work_dirs/20211018_114826.log.json --keys loss_cls loss_bbox --out work_dirs/losses.pdf

6. Result Analysis（报错，页面太小）

python tools/analysis_tools/analyze_results.py work_dirs/faster_rcnn_r50_fpn_1x_coco.py work_dirs/faster_rcnn_coco_result.pkl work_dirs/show_dir

7. Visualize Datasets（显示images和GTs）

python tools/misc/browse_dataset.py configs/_base_/datasets/coco_detection.py --output-dir work_dir

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