Codebase for ContPhy dataset generation.
Zhicheng Zheng*, Xin Yan*, Zhenfang Chen*, Jingzhou Wang, Qin Zhi Eddie Lim, Joshua B. Tenenbaum, and Chuang Gan (* denotes equal contributions)
ICML 2024
Links | Project Page | Paper (Arxiv) | Dataset Download | Cite ContPhy
News 2024/08/31: All the experiment codes and our preliminary model ContPRO are now released! Click here
Generation Tutorial | Postprocessing | Read Data | Dataset Notes | Manual Bug Fixes | Citation
If you are a beginner to Unity/C# development, familiarizing with the ContPhy dataset generation and customization logic through the user-friendly Unity Editor could quickly get you started and facilitate advanced programming.
The steps to run generation pipeline:
-
Download Unity3D
version 2021.3.17
. Recommend to install inUnity Hub
. -
(Optional) Install
DOTNET
sdk, install VSCode C#/Unity plugins.
-
Open Unity Hub, start a
New Project
. -
Choose a HDRP (High Definition Render Pipeline) template, for example, a blank HDRP template named
High Definition 3D
. -
Name the project, for example,
TestContPhy
.
Note: The complete ContPhy dataset generation depends on some commercial packages, whose legitimate licenses should be obtained at the Unity Asset Store
. Add or remove dependencies according to the requirement of your customized dataset. One can also modify the codebase to fit in open-source alternatives.
-
a. Move all the files in this repository to the directory "TestContPhy/Assets/", like this,
cd path/to/the/project/TestContPhy git clone git@github.com:zzcnewly/ContPhy-Gen.git mv ./ContPhy-Gen/* ./Assets rm ./ContPhy-Gen
b. Install
ffmpeg
and set its path in PlacementConfig.cs.c. Edit the path to your
bash
(Linux/Unix) orcmd
(Windows) in RunCommandLine.cs -
Unity Perception 1.0.0-preview.1
Setup requires several steps.
-
Install Perception Package. In the toolbar, find
Package Manager
-> click+
->from git url
-> entercom.unity.perception
to install version1.0.0-preview.1
-
In the toolbar, find
Edit -> Project Settings -> Editor -> Asynchronous Shader Compilation
, uncheck it. -
In the toolbar, find
Edit -> Project Settings -> Perception -> Base Path
, change toTestContPhy/output/images
. If no existing folder, create one. If noPerception
option, try with restarting the editor. -
In
Assets/Settings/HDRP High Fidelity.asset
in theProject
window, setLit Shader Mode
toBoth
.
-
-
Computational Geometry Unity Library:
Required. From Github. Move
Assets/_Habrador Computational Geometry Library
to theAssets
folder. -
Required. From Github. Go to the
Assets
folder. Then git clone the repo.
These packages are optional when generating a new customized dataset but required when generating ContPhy dataset.
Note: Missing the following packages may lead to compile errors. If you do not require a specific package, comment out its associated code by "//
".
-
The tool is used to convert object meshes to 3D point clouds. Import from Unity Assets Store.
If you do not require generating 3D point clouds, comment line 13, 99-112 in BaseManager.cs.
Actually there are some free tools that can serve as an alternative, for example, unity-voxel at Github.
-
Filo - The Cable Simulator 1.4
For the scenario "rope-pulley system". Import from Unity Assets Store.
Manual Bug Fixes: Check here. There are some bugs in the original codebase, we need to fix them by ourselves.
-
Obi Fluid 6.5.1 + Obi Cloth 6.5.1 + Obi Softbody 6.5.1
3 packages respectively serve for the scenario "fluid", "cloth", and "soft ball". Import from Unity Assets Store, better to follow the sequence above.
-
Ignis - Interactive Fire - URPHDRP v2.1.6
For fire simulation. Import from Unity Assets Store. We developed a fire physical reasoning scenario based on this fire simulation engine.
Manual Bug Fixes: Version 2.1.6 is not bug free. Check Manual Bug Fixes to fix bugs.
-
Restart the
Unity Editor
. -
Check there is no compile error now. If the error is from the scenario or code unrelated to your needs, comment the source code to remove the error reports.
-
According to which scenario data is to be generated, modify the class name in
MainDataGeneration.cs (line 16)
. -
In editor
Project
window, open the fileAssets/Scenes/main.unity
. -
In editor
Game
window, choose the image quality, here we chooseFullHD(1920x1080)
. -
Click the triangular button
play
to run generation. Click the square buttonstop
to stop generation. -
Check dataset in
TestContPhy/output/
. If having error generating videos, deleteTestContPhy/output/images/solo
folder and try to run again. -
explore and modify generation parameters in the files under
TestContPhy/Assets/Scripts/Configs
, for example,// generate 2000 videos with complete annotations/sensor-outputs public const int ValidIterNum = 2000; // set a random seed for generation public const int randomSeed =5834; // set dataset folder name public const string pre_name = "fluid_slides"; ...
-
Close editor
Scene
window to slightly accelerate rendering speed. For higher performance, you may want to deploy the project to cluster server.
If you are an experienced Unity/C# developer, you can scale up the dataset on servers, e.g. high-performance computing clusters. But note that the simulation and rendering jobs in this codebase have not been optimized for GPU computing and demand more CPU resources than GPU.
The launch command might be like this:
path/to/Unity/Hub/Editor/2021.3.17f1/Editor/Unity -openfile "path/to/TestContPhy/Assets/Scenes/main.unity" -executeMethod EnterBatchMode.PlayScene
For other tips, check Using Unity3D Editor.
After generation, run postprocessing script to filter valid trials.
python path/to/TestContPhy/Assets/Scripts/Python/postprocess.py --origin path/to/original/data/folder --output path/to/processed/data/folder
# for example
cd path/to/TestContPhy
python ./Assets/Scripts/Python/postprocess.py --origin ./output/fluid_slides --output ./output/fluid_slides_new
The annotations are provided in a human-readable JSON format. Additionally, a demonstration script is included to facilitate loading the dataset and visualizing its structure and dimensions.
Note: Check data structure and shapes in
Print.md
.
# for example,
# only print shapes
cd path/to/TestContPhy
python ./Assets/Scripts/Python/read_and_visualize_data.py --trial_path ./output/fluid_slides_new/0 --print_shapes
# print shapes, plot the point clouds for each frame, and directly show a selected frame.
python ./Assets/Scripts/Python/read_and_visualize_data.py --trial_path ./output/fluid_slides_new/0 --print_shapes --visualize_frame --plot_save_path ./output/images/cache --selected_frame 40
We are working with .mp4
formatted videos captured at 30
frames per second, comprising 500
videos with fixed lengths specific to each scenario: 250
frames for fluids, 150
for ropes, 145
for cloths, and 120
for balls. However, upon decoding the videos into frames and running the data loading code to fetch the sensor data, please observe the following guidelines:
-
If there is a discrepancy of
2
frames fewer than the specified numbers for any scenario, align the$n^{th}$ frame of each video with the$(n+2)^{th}$ index of the corresponding sensor data. -
In instances where there is a variation in the number of frames for particle/mesh sensor data among different objects within the same video—particularly noticeable when the duration of cloth frames is not synchronized with other objects—consider the
$30^{th}$ frame as the start time for the cloths. -
We have identified a bug where rigid objects may display
incorrect poses
in the cloth scenario. We will address and resolve this issue shortly.
Should you have any confusions or problems, please open an issue under this repo. Thanks!
# If the package "Filo" is imported, fix the following bugs.
# In the file "TestContPhy/Assets/FiloCables/Scripts/Cable.cs"
# Line 353
- float distance = link.body.SurfaceDistance(t1.Value, t2.Value, !link.orientation, false);
- link.body.AppendSamples(sampledCable, t1.Value, distance, 0, false, link.orientation);
+ //Fixed for consistancy of rope length when rolling
+ link.body.AppendSamples(sampledCable, t1.Value, link.storedCable, 0, false, link.orientation);
# Line 696
+ if (body.name != currentJoint.body1.name && body.name != currentJoint.body2.name)
// Only split if the body is a disc or a convex shape, and the raycast hit is sane.
if ((body is CableDisc || body is CableShape) && hit.distance > 0.1f && hit.distance + 0.1f < currentJoint.length)
# Line 804
// Sample the link, except if the cable is closed and this is the first link.
if (!(i == 0 && closed) || links[i].type == Link.LinkType.Attachment || links[i].type == Link.LinkType.Pinhole)
+ {
+ // Rolling links (only mid-cable)
+ if (links[i].type == Link.LinkType.Rolling)
+ {
+ Vector3? t1 = null, t2 = null;
+ if (prevJoint != null)
+ t1 = prevJoint.body2.WorldToCable(prevJoint.WorldSpaceAttachment2);
+ if (nextJoint != null)
+ t2 = nextJoint.body1.WorldToCable(nextJoint.WorldSpaceAttachment1);
+ if (t1.HasValue && t2.HasValue)
+ {
+ float distance = links[i].body.SurfaceDistance(t1.Value, t2.Value, !links[i].orientation, false);
+ if (links[i].storedCable < distance){
+ var link0 = links[i];
+ link0.storedCable = distance;
+ links[i] = link0;
+ }
+ }
+ }
SampleLink(prevJoint, links[i], nextJoint);
+ }
# If the package "Ignis" is imported, fix the following bug.
# In the file "TestContPhy/Assets/OAVA-Flame/Scripts/Engine/FireTrigger.cs"
Line 137
- Vector3 closestPoint = other.ClosestPointOnBounds(transform.position);
+ FireRecorder fr = flameObj.GetComponent<FireRecorder>();
+ Vector3 closestPoint = (fr != null&&fr.touchPoints.ContainsKey(other.name))? fr.touchPoints[other.name]: other.ClosestPointOnBounds(transform.position);
Welcome to cite ContPhy
if you find the paper, dataset, and implementations useful in your research :)
@inproceedings{zheng2024contphy,
title={ContPhy: Continuum Physical Concept Learning and Reasoning from Videos},
author={Zheng, Zhicheng and Yan, Xin and Chen, Zhenfang and Wang, Jingzhou and Lim, Qin Zhi Eddie and Tenenbaum, Joshua B and Gan, Chuang},
booktitle={International Conference on Machine Learning},
year={2024},
organization={PMLR}
}