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act_xsa)whatiname/lehome_submission_ply100pip install lerobotact_xsa). Install the provided policy package:1cd lerobot_policy_act_xsa
2pip install -e .scripts/eval_policy/lerobot_policy.py to register the act_xsa policy:1# In scripts/eval_policy/lerobot_policy.py, add this line with other imports:
2import lerobot_policy_act_xsa # Register custom act_xsa policyconfig.json uses "type": "act_xsa". This import registers act_xsa as a valid policy type in LeRobot's configuration system. Without it, you will get:Couldn't find a choice class for 'act_xsa' in <class 'lerobot.configs.policies.PreTrainedConfig'>pretrained_model/
├── config.json # Policy config (type: "act_xsa")
├── model.safetensors # Model weights
├── train_config.json # Training configuration
├── policy_preprocessor.json # Observation preprocessor
├── policy_postprocessor.json # Action postprocessor
├── policy_preprocessor_step_*.safetensors # Preprocessor weights
├── policy_postprocessor_step_*.safetensors # Postprocessor weights
└── lerobot_policy_act_xsa/ # Custom policy package (install this!)
├── pyproject.toml
└── src/
└── lerobot_policy_act_xsa/
├── __init__.py
├── configuration_act_xsa.py
├── modeling_act_xsa.py
└── processor_act_xsa.py1cd lehome-challenge
2
3python -m scripts.eval \
4 --policy_type lerobot \
5 --policy_path /path/to/downloaded/pretrained_model \
6 --garment_type "top_long" \
7 --dataset_root Datasets/example/top_long_merged \
8 --num_episodes 5 \
9 --enable_cameras \
10 --device cputop_long, top_short, pant_long, pant_shortact_xsa)whatiname/lehome_submission_ply100pip install lerobotact_xsa)，需要安装提供的策略包：1cd lerobot_policy_act_xsa
2pip install -e .scripts/eval_policy/lerobot_policy.py 中添加一行代码以注册 act_xsa 策略：1# 在 scripts/eval_policy/lerobot_policy.py 中，与其他 import 一起添加：
2import lerobot_policy_act_xsa # Register custom act_xsa policyconfig.json 中使用的是 "type": "act_xsa"。这行 import 会将 act_xsa 注册为 LeRobot 配置系统中的有效策略类型。如果没有这行代码，会报错：Couldn't find a choice class for 'act_xsa' in <class 'lerobot.configs.policies.PreTrainedConfig'>pretrained_model/
├── config.json # 策略配置（type: "act_xsa"）
├── model.safetensors # 模型权重
├── train_config.json # 训练配置
├── policy_preprocessor.json # 观测预处理器
├── policy_postprocessor.json # 动作后处理器
├── policy_preprocessor_step_*.safetensors # 预处理器权重
├── policy_postprocessor_step_*.safetensors # 后处理器权重
└── lerobot_policy_act_xsa/ # 自定义策略包（必须安装！）
├── pyproject.toml
└── src/
└── lerobot_policy_act_xsa/
├── __init__.py
├── configuration_act_xsa.py
├── modeling_act_xsa.py
└── processor_act_xsa.py1cd lehome-challenge
2
3python -m scripts.eval \
4 --policy_type lerobot \
5 --policy_path /path/to/downloaded/pretrained_model \
6 --garment_type "top_long" \
7 --dataset_root Datasets/example/top_long_merged \
8 --num_episodes 5 \
9 --enable_cameras \
10 --device cputop_long、top_short、pant_long、pant_short