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README.md

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## Examples
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- Environment interactive visualization and manual control: see [`ManiSkill2_real2sim/mani_skill2_real2sim/examples/demo_manual_control_custom_envs.py`](https://github.com/simpler-env/ManiSkill2_real2sim/blob/main/mani_skill2_real2sim/examples/demo_manual_control_custom_envs.py)
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- Simple RT-1 and Octo evaluation script on prepackaged environments with visual matching evaluation setup: see [`simpler_env/simple_inference_visual_matching_prepackaged_envs.py`](https://github.com/simpler-env/SimplerEnv/blob/main/simpler_env/simple_inference_visual_matching_prepackaged_envs.py).
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- Colab notebook for RT-1 and Octo inference: see [this link](https://colab.research.google.com/github/simpler-env/SimplerEnv/blob/main/example.ipynb).
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- Environment interactive visualization and manual control: see [`ManiSkill2_real2sim/mani_skill2_real2sim/examples/demo_manual_control_custom_envs.py`](https://github.com/simpler-env/ManiSkill2_real2sim/blob/main/mani_skill2_real2sim/examples/demo_manual_control_custom_envs.py)
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- Policy inference scripts to reproduce our Google Robot and WidowX real-to-sim evaluation results with sweeps over object / robot poses and advanced loggings. These contain both visual matching and variant aggregation evaluation setups along with RT-1, RT-1-X, and Octo policies. See [`scripts/`](https://github.com/simpler-env/SimplerEnv/tree/main/scripts).
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- Real-to-sim evaluation videos from running `scripts/*.sh`: see [this link](https://huggingface.co/datasets/xuanlinli17/simpler-env-eval-example-videos/tree/main).
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