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Published 20 hours ago • verified publisher icon chenqi1126

The evaluation of COCO14 segmentation masks

Open mt-cly opened this issue 2 years ago • 3 comments

Hi, thanks for your great work. Your SIPE achieves considerable performance in COCO14 val set. I wonder how to obtain the image GT for COCO14 so that I can calculate miou as done in https://github.com/chenqi1126/SIPE/blob/main/eval_cam.py#L52 . As the COCO official only provides the .json file, can you please tell me how to translate the .json to .png? Thanks.

mt-cly avatar Oct 30 '22 15:10 mt-cly

Hi @mt-cly, Thanks for your attention. You can use 'pycocotools' to convert annotation to png. An off-the-shelf code: https://github.com/zhaozhengChen/ReCAM/blob/main/mscoco/annToMask.py.

chenqi1126 avatar Oct 31 '22 07:10 chenqi1126

Thanks for your reply.

mt-cly avatar Nov 02 '22 08:11 mt-cly

I meet another question, I directly use your provide deeplab_r38_coco.pth on the modified code of seamv1, but I can only achieve around 36% mIoU, (+CRF ~37% mIoU), still has a large gap with reported 43.6%, I have no idea about that, have you any suggestions? Or can you provide the evaluation code for COCO14 val set? Thanks.

mt-cly avatar Feb 12 '23 07:02 mt-cly