Release ActiveScale checkpoints

.gitattributes

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NOTICE

@@ -0,0 +1,21 @@
+ActiveScale
+
+This product includes software developed by Physical Intelligence and released
+in the openpi repository under the Apache License 2.0:
+https://github.com/Physical-Intelligence/openpi
+
+The ActiveScale development branch imported its openpi/pi0.5 base at fork
+commit ad5ad045b0ac0c5bab05d951c426716aae40bf08. During public-release
+preparation, the inherited tree and licenses were cross-checked against openpi
+commit 215abfb217dbac7d5f1273282331b9b1866c0479.
+
+ActiveScale modifies the openpi PyTorch pi0.5 implementation by adding temporal
+camera history, camera tokens and pose prediction, mixed human/robot data
+adapters, joint training objectives, and an exact packed attention path.
+
+Gemma components remain subject to the terms in LICENSE_GEMMA.txt. Third-party
+datasets, robot drivers, headset runtimes, and checkpoints retain their own
+licenses and are not relicensed by this repository.
+
+Gemma is provided under and subject to the Gemma Terms of Use found at
+ai.google.dev/gemma/terms.

README.md

@@ -0,0 +1,55 @@
+---
+library_name: openpi
+license: other
+license_name: gemma-terms
+license_link: https://ai.google.dev/gemma/terms
+pipeline_tag: robotics
+---
+
+<h1 align="center">ActiveScale: Scaling Active Perception for Robots<br>across Model, Data, and Hardware</h1>
+
+<p align="center">
+  <a href="https://arxiv.org/abs/2609.18514"><img src="https://img.shields.io/badge/arXiv-B31B1B?style=for-the-badge&logo=arxiv&logoColor=white" alt="arXiv"></a>
+  <a href="https://active-scale.github.io/"><img src="https://img.shields.io/badge/Project_Page-4285F4?style=for-the-badge&logo=googlechrome&logoColor=white" alt="Project page"></a>
+  <a href="https://youtu.be/Iya0bSZ8Dko"><img src="https://img.shields.io/badge/YouTube-FF0000?style=for-the-badge&logo=youtube&logoColor=white" alt="YouTube"></a>
+  <a href="https://huggingface.co/davidzhou302/ActiveScale"><img src="https://img.shields.io/badge/Hugging_Face-FFD21E?style=for-the-badge&logo=huggingface&logoColor=black" alt="Hugging Face"></a>
+  <a href="https://modelscope.cn/datasets/shuai302/ActiveScale"><img src="https://img.shields.io/badge/ModelScope-624AFF?style=for-the-badge" alt="ModelScope"></a>
+</p>
+
+<p align="center">
+  <a href="https://youtu.be/Iya0bSZ8Dko">
+    <img src="https://img.youtube.com/vi/Iya0bSZ8Dko/maxresdefault.jpg" alt="ActiveScale video" width="100%">
+  </a>
+</p>
+
+<p align="center">
+  <a href="https://active-scale.github.io/">
+    <img src="https://raw.githubusercontent.com/active-scale/active-scale.github.io/main/assets/teaser.webp" alt="ActiveScale overview" width="100%">
+  </a>
+</p>
+
+<p align="center">
+  ActiveScale presents a scalable way to study active perception for robot manipulation across model, data, and hardware.<br>
+  It equips a vision-language-action model with temporal camera observations and camera-pose prediction,<br>
+  and introduces the Active-perception Mobile-manipulation Platform (AMP) for coordinated viewpoint and manipulation control.
+</p>
+
+<h2 align="center">Checkpoints</h2>
+
+<table align="center">
+  <thead>
+    <tr><th>Checkpoint</th><th>Description</th></tr>
+  </thead>
+  <tbody>
+    <tr><td><code>midtraining</code></td><td>Mid-training checkpoint</td></tr>
+    <tr><td><code>bag</code></td><td>Bag task checkpoint</td></tr>
+    <tr><td><code>drawer</code></td><td>Drawer task checkpoint</td></tr>
+    <tr><td><code>pot</code></td><td>Pot task checkpoint</td></tr>
+    <tr><td><code>box</code></td><td>Box task checkpoint</td></tr>
+    <tr><td><code>under</code></td><td>Under-table task checkpoint</td></tr>
+  </tbody>
+</table>
+
+<p align="center">
+  Code and usage: <a href="https://github.com/ShuaiZhou302/ActiveScale">github.com/ShuaiZhou302/ActiveScale</a>
+</p>

bag/assets/cobot-avp-teleop_lerobot_task0_bag_camera_clean_v2/norm_stats.json

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