weigq / 3d_pose_baseline_pytorch

A simple baseline for 3d human pose estimation in PyTorch.
MIT License
367 stars 66 forks source link

Pre-processed data #1

Closed macaodha closed 6 years ago

macaodha commented 6 years ago

Hi there,

Your code looks great. I was just wondering what is the main difference between your pre-processed dataset and h36m.zip from the original tensorflow repo.

Thanks

weigq commented 6 years ago

actually, it is same as the original repo. It is the normalized data.

best.

macaodha commented 6 years ago

So it's the same as running their data loading and then preprocessing code (e.g. including projection, keypoint exclusion, etc)?

Thanks

weigq commented 6 years ago

yes

macaodha commented 6 years ago

Thanks for all your help. When I load the data with your code it is the following size: Train size 1559752 Test size 548819

From the original tensorflow the train is the same but the test is bigger: Test size 550644

Any ideas why it might be different.

weigq commented 6 years ago

sorry, I have fixed this and updated the data.

The videos provided by the Human3.6M contain a damaged video, so the test set is less if using stacked hourglass to predict 2d pose, and I mistakenly missed this one when processing groundtruth data.

I will upload the data processing code. Thanks!

macaodha commented 6 years ago

Thanks

salihkaragoz commented 6 years ago

@weigq, @macaodha Btw, as a supplementary information;

This action has no video in the Human3.6M dataset, Subject 11 Action Directions Camera 54138969 (no video)

These below actions has smaller annotations than expected in the global coordinate, not image plane Subject 9 Action Greeting Subject 9 Action SittingDown_1 Subject 9 Action Waiting_1 Subject 9 Action Walking

Good Work!

weigq commented 6 years ago

@salihkaragoz Great! Thanks for your supplements.

weigq commented 6 years ago

I will closed this issue, you can reopen it if needed.