Add rotated_bbox_calibration #7
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First, you can obtain a DOTA_1.0.json file in coco-style after modifying the CocoConvert.py in dotadevkit, as written in tools/dotadevkit.py, some thing like this: {'image_id': 25, 'score': 0.97, 'bbox': [385.79, 1783.79, 407.02, 1137.92, 89.9, 1127.49, 68.66, 1773.36], 'category_id': 4}.
Then, you should use tools/dota2coco_val_bbox.py to get coco-style detection results on valid set.
Finally, you can get a calibrator using tools/analysis_tools/model_calibration_rotate.py in which I modified the bbox_overlaps() to box_iou_quadri() to compute rotated bounding box ious.
I got the same calibrator provided in the zip file and reproduce the results in Table 9.
Please modify the file path first when calibrating your own object detectors!