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[wangdong0556]

Thank you for providing this function. Where can I find name_of_input_pose. Json and result.json ? Can you provide the download address

[mks0601]

you can use any 2D pose estimation methods to obtain name_of_inptu_pose.json. For example, here

[wangdong0556]

Thank you for your reply, but I can't jump when I click 'here'. In addition, I saw in 'TF-Simplehumanpose' that someone asked how to find 'human_detection. Json', but it showed 'Closed this on 6 Feb 2019', 'name_of_input_pose' and 'name_of_inptu_pose' are the same?Is' result.json '2D result of' name_of_input_pose. Json '?

[metehkaya]

Can the file you provided here be directly used during training or testing? I guess, it is just a part of MS COCO json file, right? Because according to video, it seems that MS COCO compatible json file is actually larger.

[mks0601]

That file is 2D pose estimation result of other 2D pose estimator, not a part of MSCOCO dataset.
You can train and test on that file, but the trained model will not be model-agnostic refiner, while the PoseFix is.

[metehkaya]

I am aware that the data you provided is not a part of MSCOCO dataset. Actually what I ask is that should that file follow MS COCO format completely. I guess not, because you don't make COCO(name_of_inptu_pose.json) at input_pose_load function like you did at COCO(self.test_annot_path) at load_annot function.

[mks0601]

Sure. The file format of that file follows 2D pose estimation output format, used to evaluate it by COCO evaluation API. The file format is completely different from COCO(self.test_annot_path)