This repo contains code to process and render images of the MIT Pushing dataset (http://web.mit.edu/mcube//push-dataset/).
First, create a folder structure like [pushdata folder]/[surface name]/ by downloading the zip-files for each surface to [pushdata folder]/ and unzipping them there. This should result in a folder structure like this: [pushdata folder]/[surface name]/[object name]/[object_name]_h5.zip
Below we will use ~/pd as the pushdata root folder. For example, the data of rect1 on ABS surface will be at ~/pd/abs/rect1/rect1_h5.zip.
First preprocess the data using
scripts/preprocess.py --source-dir ~/pd
This will
- remove redundant data entries
- treat some (not all) of the jumps in object orientation
- transform the orientation to [-pi, pi]
- synchronize the data by resampling to a given frequency
- set the initial object position and orientation to zero
- add information about the push (angle, velocity...) to the h5 data files
This will save all the preprocessed h5 files for object [object_name] on surface [surface_name] to ~/pd/[surface name]/[object name]. If you want to write output to another directory than the source directory (~/pd), you can specify this with the --out-dir argument.
The preprocessing has to be done before.
To render RGB-D pictures from the preprocessed images, refer to
scripts/render_scene.py.
Assuming we are at the top folder of pdproc, a rendering demo can be run by
scripts/render_scene.py --source-folder ~/pd --out-dir .
This will generate a series of images in jpeg in the current folder.
To annotate the preprocessed h5 files with contact points and surface normals,
please refer to scripts/render_scene.py.