可以直接跳过微调启动模型，查看效果吗？希望可以更详细的步骤介绍

[bigsmartbig]

[bigsmartbig]

data_stats_path是指什么的路径？传入前面下载的LIBERO数据集路径可以吗

[ModiShi]

1. If you have AgiBot G1, you can directly deploy GO-1. Otherwise, you need to finetune on your dataset first.
2. When finetuning GO-1, data_stats is automatically saved alongside your checkpoint. Pass this file when deploying.

[bigsmartbig]

Could you explain what each parameter in the payload? Or where can I learn about them?

[ModiShi]

By default, the model takes three images, one instruction, and robot state (proprioception) as input to output actions. Different LeRobot datasets use different image key names (e.g., "image", "head_color"), which need to be specified in the config. You can also use fewer than 3 images, as shown in our Libero example. The ctrl_freqs parameter sets the robot control frequency - use the default value of 30 if unsure.

[simplew2011]

payload = {
    "top": np.array(Image.open("frames/head_color.mp4_20251011_194851.031.png").convert("RGB")),
    "right": np.array(Image.open("frames/hand_right_color.mp4_20251011_194816.624.png").convert("RGB")),
    "left": np.array(Image.open("frames/hand_left_color.mp4_20251011_194739.489.png").convert("RGB")),
    "instruction": "Hanging clothes with a hanger",
    "state": np.expand_dims(np.random.rand(16), axis=0),
    "ctrl_freqs": np.array([30]),
}

[zbzyjya]

payload = {
    "top": np.array(Image.open("frames/head_color.mp4_20251011_194851.031.png").convert("RGB")),
    "right": np.array(Image.open("frames/hand_right_color.mp4_20251011_194816.624.png").convert("RGB")),
    "left": np.array(Image.open("frames/hand_left_color.mp4_20251011_194739.489.png").convert("RGB")),
    "instruction": "Hanging clothes with a hanger",
    "state": np.expand_dims(np.random.rand(16), axis=0),
    "ctrl_freqs": np.array([30]),
}

Thank you for your response. If I want to directly test the effect of the original model, how should I implement video stream input using the payload example you provided, as well as the sequential execution of the robot after the action is returned? Are there any open-source projects or modules that I can refer to?