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I haven't used cocoeval.py, but it looks like you need both the ground truth and the results to be in coco-style. I don't convert the output back into coco-style, but that's a good idea for improvement.
I'm not sure when I can get to it, but if you wanted to try and implement mask-rcnn output to coco, you could try using https://github.com/waspinator/pycococreator as a reference.
Hi waspinator
@waspinator
You write the /libraries/mextra/utils.py for model evaluating in your shape datasets. right?
But, I think the your shape datasets is coco-style.
Can I use coco-API to evaluate the model in your shape dataset?
https://github.com/nightrome/cocoapi
https://github.com/nightrome/cocoapi/blob/master/PythonAPI/pycocoEvalDemo.ipynb
How can I do this?
Could you tell me more detail?
many thanks!
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