v0.6.0

enhancement

• add coco_evaluation script, refactor coco_error_analysis script (#162)
  coco_evaluation.py script usage:

python scripts/coco_evaluation.py dataset.json results.json

will calculate coco evaluation and export them to given output folder directory.

If you want to specify mAP metric type, set it as --metric bbox mask.

If you want to also calculate classwise scores add --classwise argument.

If you want to specify max detections, set it as --proposal_nums 10 100 500.

If you want to specify a psecific IOU threshold, set it as --iou_thrs 0.5. Default includes 0.50:0.95 and 0.5 scores.

If you want to specify export directory, set it as --out_dir output/folder/directory .

coco_error_analysis.py script usage:

python scripts/coco_error_analysis.py dataset.json results.json

will calculate coco error plots and export them to given output folder directory.

If you want to specify mAP result type, set it as --types bbox mask.

If you want to export extra mAP bar plots and annotation area stats add --extraplots argument.

If you want to specify area regions, set it as --areas 1024 9216 10000000000.

If you want to specify export directory, set it as --out_dir output/folder/directory .

bugfixes

• prevent empty bbox coco json creation (#164)
• dont create mot info while when type='det' (#163)

breaking changes

• refactor predict (#161)
  By default, scripts apply both standard and sliced prediction (multi-stage inference). If you don't want to perform sliced prediction add --no_sliced_pred argument. If you don't want to perform standard prediction add --no_standard_pred argument.