Releases: obss/sahi
v0.3.7
v0.3.6
v0.3.5
v0.3.4
v0.3.3
-
refactorized Coco class, added CocoVid class
-
added coco_error_analysis.py script:
python scripts/coco_error_analysis.py results.json output/folder/directory --ann coco/annotation/path
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
.
v0.3.1
v0.3.0
Major Updates
- refactorize main predict function:
python scripts/predict.py --visual --source image/file/or/folder --model_path path/to/model --config_path path/to/config
will export predictions visuals to runs/predict/exp
folder.
If you want to export prediction pickles and cropped predictions add --pickle
and --crop
arguments.
- add option to export coco json:
python scripts/predict.py --coco_file path/to/coco/file --source coco/images/directory --model_path path/to/model --config_path path/to/config
will perform inference using provided coco file, then export results as a coco json file to runs/predict/exp/results.json
- add script for coco2yolov5 conversion:
python scripts/coco2yolov5.py --coco_file path/to/coco/file --source coco/images/directory --train_split 0.9
will convert given coco dataset to yolov5 format and export to runs/coco2yolov5/exp
folder .
Minor Updates
- add export_format to crop_object_predictions
- fix coco annotation serialization
- more generic coco handling
- add option to export visuals
- update ci/package testing workflows