ManiSkill2 is a unified benchmark for learning generalizable robotic manipulation skills powered by SAPIEN. It features 20 out-of-box task families with 2000+ diverse object models and 4M+ demonstration frames. Moreover, it empowers fast visual input learning algorithms so that a CNN-based policy can collect samples at about 2000 FPS with 1 GPU and 16 processes on a workstation. The benchmark can be used to study a wide range of algorithms: 2D & 3D vision-based reinforcement learning, imitation learning, sense-plan-act, etc.
Please refer our documentation to learn more information.
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Release files for mani-skill2 0.5.3
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| mani_skill2-0.5.3.tar.gz | 11.9 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| mani_skill2-0.5.3-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 23.9 MB
Release files / mani_skill2-0.5.3.tar.gz
| Download URL | mani_skill2-0.5.3.tar.gz |
|---|---|
| Size | 11.9 MB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
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twine/4.0.2 CPython/3.9.0
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Release files / mani_skill2-0.5.3-py3-none-any.whl
| Download URL | mani_skill2-0.5.3-py3-none-any.whl |
|---|---|
| Size | 12.0 MB |
| Tags | Python 3 |
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SHA-256 checksum How to use checksums |
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No |
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twine/4.0.2 CPython/3.9.0
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