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README.md
Interactive Lego Machine Learning Environment
LTRON is an environment for interactive machine learning assembly problems using Lego bricks. It is based on LDraw the Open Model Repository , and uses additional data from LDCAD .
If you use LTRON in acadmic work, please cite our ECCV 2022 Paper :
@inproceedings{walsman2022break, author = {Aaron Walsman, Muru Zhang, Klemen Kotar, Karthik Desingh, Ali Farhadi, Dieter Fox}, title = {Break and Make: Interactive Structural Understanding Using LEGO Bricks}, booktitle = {European Conference on Computer Vision}, year={2022} }
Examples
31025 - Mountain Hut - Mountain Hut.mpd
10030-1 - Imperial Star Destroyer - UCS.mpd
Installation:
To install LTRON run:
pip install ltron ltron_asset_installer
The first line will download LTRON from pypi and install it in your python path. The second line will download and install a set of models and part files that are necessary for LTRON. By default, these assets are installed to ~/.cache/ltron and ~/.cache/splendor. This will take around 3GB of space.
Release Versions:
ECCV 2022: (pypi 1.0.X) (branch v1.0.0)
Ongoing Work (not in pypi) (branch master)
Testing Things Out:
Once installed you should be able to run ltron_viewer to interactively inspect a lego model. For example from the top directory you can run:
ltron_viewer "~/.cache/ltron/collections/omr/ldraw/8661-1 - Carbon Star.mpd"
Or:
ltron_viewer "~/.cache/ltron/collections/omr/ldraw/75060 - Slave I.mpd"
You can interact with the model by clicking on it and dragging the mouse around. LMB - Orbit. RMB - Pan. Scroll - Zoom. There are a few keys you can press h to hide the brick you are hovering over, v to show all hidden bricks and m to switch back and forth between mask mode and regular rendering. See other options in ltron/visualization/ltron_viewer.py.
Requirements:
gym numpy pyquaternion gdown tqdm splendor-render
The splendor-render package only works on Ubuntu at the moment, and requires OpenGL 4.6. As long as you have a modern GPU with recent drivers you should be fine.
You may need to install freeglut:
sudo apt-get install freeglut3-dev
File Formats
LTRON uses the LDraw file formats (.dat, .ldr, .mpd) to describe bricks and models. We convert all bricks to obj files for use in splendor-render. These are installed to ~/.cache/splendor/ltron_assets_low or ~/.cache/splendor/ltron_assets_high.
The Open Model Repository files are installed to ~/.cache/ltron/collections/omr/ldraw.
Data Layout:
This section is current as of v1.0.X, but may be streamlined in future releases:
As noted above, the LTRON assets are placed by default in ~/.cache/ltron. This location can be changed by setting the $LTRON_HOME environment variable. Additionally, some rendering assets are placed in ~/.cache/splendor. This location can be changed by setting the $SPLENDOR_HOME` environment variable.
All LTRON datasets are registered in $LTRON_HOME/settings.cfg. In LTRON each dataset contains a json file that describes where to find the files associated with that dataset, and various metadata. These are listed in the [datasets] header in the settings.cfg file. These json files usually refer to a particular "collection" of ldraw files. You can think of a collection as a root file path where several ldraw files and/or episode zip files live. These locations are specified in the [collections] header in the settings.cfg file.
Looking the $LTRON_HOME/collections/random_construction_6_6/rc_6_6.json file we can see what kind of data it contains:
splits: a set of names corresponding to a block of files used for training or testing. rc_6_6.json contains nine splits: a train_N, test_N and train_episodes_N for N=2,4,8. The path to each of these splits starts with {random_construction_6_6}/... which tells the system to look for these files inside the random_construction_6_6 collection.
max_instances_per_scene: an upper bound on number of instances that exist in any of the ldraw files used in the dataset.
max_edges_per_scene: an upper bound on the number of connections between bricks that exist in any of the ldraw files used in this dataset.
shape_ids: a class label for each brick shape used in this dataset
class_ids: a separate class label for each brick color used in this dataset
Using this structure provides access to the following commands:
ltron.dataset.get_dataset_info('dataset_name') returns the contents of the json dataset file
ltron.dataset.get_dataset_paths('dataset_name', 'split_name', subset=None, rank=0, size=1) returns a list of paths belonging to a particular split.
ltron.dataset.get_zip_paths('dataset_name', 'split_name', subset=None, rank=0, size=1) returns a zipfile object and a list of its contents for a particular split.
LtronEnv Structure
We have tried to make the LtronEnv structure modular so that it can be customized for a variety of observation types, action spaces and tasks. Therefore the LtronEnv gym environment is a container for multiple components, each of which specify their own action/observation spaces and state variables. When LtronEnv's reset/step/etc. method is called, it executes each of its component's reset/step/etc. methods in order and accumulating the result into a dictionary based on the component's name. Currently only the Break and Make (ltron/gym/envs/break_and_make_env.py in v1.0.0) is stable.
Further Notes:
All 3D units are in LDraw LDUs . One LDU is approximately 0.4 mm, so the physical extents of these scenes can be quite large.
Disclaimer:
LTRON is based entirely on fan-made content with open licensing, and is not associated with the LEGO group in any way.
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