Bump version to 0.4.0

haosulab · Feb 10, 2023 · 65d2063 · 65d2063
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diff --git a/README.md b/README.md
@@ -1,14 +1,13 @@
 # ManiSkill2
 
-![teaser](figures/teaser.jpg)
+![teaser](figures/teaser_v2.jpg)
 
 [![PyPI version](https://badge.fury.io/py/mani-skill2.svg)](https://badge.fury.io/py/mani-skill2)
 [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/haosulab/ManiSkill2/blob/main/examples/tutorials/1_quickstart.ipynb)
 [![Docs status](https://img.shields.io/badge/docs-passing-brightgreen.svg)](https://haosulab.github.io/ManiSkill2)
 <!-- [![Docs](https://github.com/haosulab/ManiSkill2/actions/workflows/gh-pages.yml/badge.svg)](https://haosulab.github.io/ManiSkill2) -->
 
-ManiSkill2 is a unified benchmark for learning generalizable robotic manipulation skills powered by [SAPIEN](https://sapien.ucsd.edu/). **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.
+ManiSkill2 is a unified benchmark for learning generalizable robotic manipulation skills powered by [SAPIEN](https://sapien.ucsd.edu/). **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](https://haosulab.github.io/ManiSkill2) to learn more information.
 

diff --git a/figures/teaser.jpg → figures/teaser_v2.jpg b/figures/teaser.jpg → figures/teaser_v2.jpg
diff --git a/requirements.txt b/requirements.txt
@@ -2,7 +2,7 @@
 numpy<1.24
 scipy
 gym>=0.18.3,<=0.21.0
-sapien>=2.2.1
+sapien==2.2.1
 # basic
 h5py
 pyyaml

diff --git a/setup.py b/setup.py
@@ -1,6 +1,8 @@
 from setuptools import find_packages, setup
 
-long_description = """ManiSkill2 is a large-scale robotic manipulation benchmark, focusing on learning generalizable robot agents and manipulation skills. It features 2000+ diverse objects, 20 task categories, and a large-scale demonstration set in [SAPIEN](https://sapien.ucsd.edu/), a fully-physical, realistic simulator. The benchmark can be used to study 2D & 3D vision-based imitation learning, reinforcement learning, and motion planning, etc."""
+long_description = """ManiSkill2 is a unified benchmark for learning generalizable robotic manipulation skills powered by [SAPIEN](https://sapien.ucsd.edu/). **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](https://haosulab.github.io/ManiSkill2) to learn more information."""
 
 
 def read_requirements():
@@ -12,7 +14,7 @@ def read_requirements():
 
 setup(
     name="mani_skill2",
-    version="0.3.3",
+    version="0.4.0",
     description="ManiSkill2: A Unified Benchmark for Generalizable Manipulation Skills",
     long_description=long_description,
     long_description_content_type="text/markdown",