About how to apply this work on my own data? about posefix_release HOT 17 CLOSED

I cannot understand what you asked

sorry，maybe I need to understand how to transform dataset format again. I feel so sorry about disturbing you. Happy Christmas Eve！

from posefix_release.

You can see this code. Once you convert your dataset to MSCOCO format, you can easily adapt that code to use your dataset.

from posefix_release.

from posefix_release.

Hello, I also meet a problem that my own dataset how to get annotations? or this file is not needed?Thanks.

from posefix_release.

I cannot understand what you asked

from posefix_release.

Hello, I want to ask a question that my own data also need annotations file like COCO's person_keypoints_val2017.json?

from posefix_release.

Right. You should convert annotation of your own dataset to MSCOCO format.

from posefix_release.

Maybe these codes would be helpful.
https://github.com/mks0601/TF-SimpleHumanPose/tree/master/tool

These codes convert mpii or posetrack datasets to coco format.

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Thanks a lot, I will try!

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Hello, I used coco2017val dataset to get results from TF-simple pose, then take it as input_pose.json, but also appear "FileNotFoundError: [Errno 2] No such file or directory: 'tmp_result_0.pkl" ,I don't know how to deal with it. Please give me some advices, thank you very much!

from posefix_release.

The tmp_result_0.pkl is a just temporal file, which is automatically generated during testing. You should set proper dataset and testset in main/config.py and proper path in data/COCO/dataset.py.

from posefix_release.

The tmp_result_0.pkl is a just temporal file, which is automatically generated during testing. You should set proper dataset and testset in main/config.py and proper path in data/COCO/dataset.py.

Thank you, my problem has solved.

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@mks0601 Hi, Could you please tell me how to generate /test_on_trainset/result.json in my own dataset.
Could I produce it by TF-SimpleHumanPose?, It is indispensable? and what's it role?

from posefix_release.

Most of the images do not have all keypoint coordinate annotations because of truncations or severe occlusions. I used test_on_trainset to fill the not annotated keypoint coordinates. The format of the .json file exactly follows MSCOCO format. You can use any human pose estimation method to get it.

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@mks0601 Thanks your kind respond, Do you mean that original coordinate annotations may not include all keypoints, So the function of test_on_trainset is to mitigate the problem ?

from posefix_release.

Yes. For example, the annotation file of COCO dataset contains keypoints like the below figure.

Among x1, y1, v1, ..., v1 provides the below information.

Each keypoint has a 0-indexed location x,y and a visibility flag v defined as v=0: not labeled (in which case x=y=0), v=1: labeled but not visible, and v=2: labeled and visible.

If v==0, the coordinates are not annotated, which requires test_on_trainset.

from posefix_release.

So kind of you, thanks!

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