Use own images

Hi, I am interested in testing your network on my own images.

According to your answer on other questions here, one should use Stacked Hourglass to get predictions in 2D. That I have done and saved them in .h5 format.

I have also changed a bit in your code so that I do not need the 3D groundtruth in order to evaluate the loss.

The code now runs and uses my saved h5-files from Stacked Hourglass. However, the output 3D poses are completely messed up.

I have unNormalized the predicted 3D pose using the training data by calling:

    _, _, data_mean_3d, data_std_3d, dim_to_ignore_3d, dim_to_use_3d, train_root_positions, test_root_positions = data_utils.read_3d_data(
    actions, FLAGS.data_dir, FLAGS.camera_frame, rcams, FLAGS.predict_14 )

I attach a file for how the 2D-predictions look like and the resulting 3D pose.

[ArashHosseini]

@una-dinosauria, thanks for the link, I have followed his instructions and can speak of a happy outcome. sandbox under forked Repo checkout output please, thx.

[liuyu666-thu]

Hi, @ArashHosseini @liuyu666-thu I wanted to test my own videos based on both open pose and stacked hour glass network if possible. I wanted to test it on videos stored locally on my PC . Can you guys guide me through it ? I am quite new to this topic.

You can have a try on Arash’s great repo https://github.com/ArashHosseini/3d-pose-baseline. First use openpose to get 2D keypoints and write the results out in json format and then run Arash’s code. For detailed guide, you may refer to his README.