README: official RMBench dataset, usage matching the CAMP repository

README.md

@@ -25,6 +25,8 @@ tags:
   <a href="https://robo-camp.github.io/"><img alt="Project page" src="https://img.shields.io/badge/Project-Page-2f6fe4?logo=googlechrome&logoColor=white"></a>
   &nbsp;
   <a href="https://github.com/RoboTwin-Platform/RMBench"><img alt="RMBench" src="https://img.shields.io/badge/Benchmark-RMBench-6a3fb5"></a>
+  &nbsp;
+  <a href="https://huggingface.co/datasets/TianxingChen/RMBench"><img alt="RMBench dataset" src="https://img.shields.io/badge/%F0%9F%A4%97%20Dataset-TianxingChen%2FRMBench-ffbf00"></a>
 </p>
 
 <p align="center">
@@ -41,7 +43,9 @@ current image does not determine the next action.
 
 This repository holds the CAMP policies for all nine tasks of **[RMBench](https://github.com/RoboTwin-Platform/RMBench)**,
 a memory-dependent bimanual manipulation benchmark built on RoboTwin 2.0 (Aloha-AgileX dual-arm robot). Every
-policy is trained from the 50 demonstrations RMBench releases per task and evaluated with RMBench's own protocol.
+policy is trained from the official RMBench demonstrations
+([`TianxingChen/RMBench`](https://huggingface.co/datasets/TianxingChen/RMBench), `demo_clean`, 50 per task)
+and evaluated with RMBench's own protocol.
 The files contain inference weights only.
 
 ## 📊 Results
@@ -211,26 +215,30 @@ bookkeeping.
 
 ## 🚀 Usage
 
-The evaluation code is in [`scripts/rmbench/eval`](https://github.com/KuanchengWang/CAMP) of the CAMP repository.
-It includes a Docker launcher for RMBench and the `policy_CAMP` adapter, which implements RMBench's
-`get_model / eval / reset_model` interface.
+Evaluation code, training launcher and full instructions are in the
+[RMBench section of the CAMP repository](https://github.com/KuanchengWang/CAMP#-rmbench). To evaluate
+one task on the 100 standard test seeds:
 
 ```bash
-# 1. download the checkpoints
-huggingface-cli download harrywang01/CAMP-RMBench-Checkpoints --local-dir camp_rmbench
+git clone --recurse-submodules https://github.com/KuanchengWang/CAMP.git && cd CAMP
+./docker_run.sh build && docker build -f docker/Dockerfile.rmbench -t camp-rmbench:latest .
+git clone https://github.com/RoboTwin-Platform/RMBench ~/rmbench && (cd ~/rmbench && bash script/_download_assets.sh)
 
-# 2. arrange one task in the layout the evaluator expects
+huggingface-cli download harrywang01/CAMP-RMBench-Checkpoints --local-dir ckpts/hf
 T=swap_T
 mkdir -p ckpts/stage2/$T/checkpoints ckpts/stage1/$T
-cp camp_rmbench/$T/policy.ckpt  ckpts/stage2/$T/checkpoints/policy.ckpt
-cp camp_rmbench/$T/memory/*     ckpts/stage1/$T/
+cp ckpts/hf/$T/policy.ckpt ckpts/stage2/$T/checkpoints/policy.ckpt
+cp ckpts/hf/$T/memory/*    ckpts/stage1/$T/
 
-# 3. evaluate on 100 RMBench test seeds (run from the CAMP repository)
-STAGE1=$PWD/ckpts/stage1 STAGE2=$PWD/ckpts/stage2 \
-  scripts/rmbench/eval/docker_rmbench.sh python /workspace/scripts/rmbench/eval/rmbench_eval.py \
-  eval --task $T --ckpt policy --episodes 100
+export RMBENCH=~/rmbench STAGE1=$PWD/ckpts/stage1 STAGE2=$PWD/ckpts/stage2 EVAL_OUT=$PWD/data/rmbench_eval
+E=scripts/rmbench/eval
+$E/docker_rmbench.sh python /workspace/$E/rmbench_eval.py seeds --task $T               # the 100 expert-solvable test seeds
+$E/docker_rmbench.sh python /workspace/$E/rmbench_eval.py eval  --task $T --ckpt policy  # -> data/rmbench_eval/results/$T/policy/results.json
 ```
 
+To retrain a task from the official demonstrations with the same settings, run
+`bash scripts/rmbench/train_rmbench.sh <task>` inside the `camp` container.
+
 ## 📝 Citation
 
 If you find CAMP useful, please cite: