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Nikodem Bartnik
2026-05-14 09:26:27 +02:00
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@@ -76,44 +76,44 @@ lerobot-record \
While collecting the dataset you can control the process with your keyboard: While collecting the dataset you can control the process with your keyboard:
Control the data recording flow using keyboard shortcuts: Control the data recording flow using keyboard shortcuts:
- Press **Right Arrow (```→```)**: Early stop the current episode or reset time and move to the next. - Press **Right Arrow (```→```)**: Save episode and move to the next.
- Press **Left Arrow (```←```)**: Cancel the current episode and re-record it. - Press **Left Arrow (```←```)**: Delete current episode and retry.
- Press **Escape (```ESC```)**: Immediately stop the session, encode videos, and upload the dataset. - Press **Escape (```ESC```)**: Stop, encode videos, and upload.
### Training ### Training
Depending on your hardware training the policy might take a few hours. Depending on your hardware training the policy might take a few hours.
``` ```
lerobot-train \ lerobot-train \
--dataset.repo_id=${HF_USER}/so101_dataset_test \ --dataset.repo_id=${HF_USER}/so101_dataset_test \
--policy.type=act \ --policy.type=act \
--output_dir=outputs/train/act_so101_test \ --output_dir=outputs/train/act_so101_test \
--job_name=act_so101_test \ --job_name=act_so101_test \
--policy.device=cuda \ --policy.device=cuda \
--wandb.enable=true \ --wandb.enable=true \
--policy.repo_id=${HF_USER}/policy_test \ --policy.repo_id=${HF_USER}/policy_test \
--steps=20000 --steps=20000
``` ```
- Policy Types: ```act```, ```diffusion```, ```smolvla```, ```pi05```
- Devices: ```cuda``` (NVIDIA), ```mps``` (Apple Silicon), ```cpu```
What you can change:
- polic.type: act, smolvla, pi05
- policy.device: cuda, mps, cpu
- number of steps: how long will the model train
### Inference ### Inference
Inference means running the trained policy/model on a robot. For that we use ```lerobot-rollout```. You will need to provide a path to your policy. It can be a local path or a path to Hugging Face for example "lerobot/folding_latest". Your cameras configuration need to match what was used when collecting the dataset. Duration is in seconds if unspecified it will run forever. Inference means running the trained policy/model on a robot. For that we use ```lerobot-rollout```. You will need to provide a path to your policy. It can be a local path or a path to Hugging Face for example "lerobot/folding_latest". Your cameras configuration needs to match what was used when collecting the dataset. Duration is in seconds if unspecified, it will run forever.
> [!TIP] > [!TIP]
> If you are using the previous release V0.5.1 instead of ```lerobot-rollout``` you need to use ```lerobot-record``` > If you are using the previous release V0.5.1 instead of ```lerobot-rollout``` you need to use ```lerobot-record```. More information [here](https://huggingface.co/docs/lerobot/v0.5.1/en/il_robots#run-inference-and-evaluate-your-policy).
``` bash ``` bash
lerobot-rollout \ lerobot-rollout \
--strategy.type=base \ --strategy.type=base \
--policy.path=${HF_USER}/my_policy \ --policy.path=${HF_USER}/my_policy \
--robot.type=so101_follower \ --robot.type=so101_follower \
--robot.port=/dev/ttyACM1 \ --robot.port=/dev/ttyACM1 \
--robot.cameras="{ up: {type: opencv, index_or_path: /dev/video1, width: 640, height: 480, fps: 30}, side: {type: opencv, index_or_path: /dev/video5, width: 640, height: 480, fps: 30}}" \ --robot.cameras="{ up: {type: opencv, index_or_path: /dev/video1, width: 640, height: 480, fps: 30}, side: {type: opencv, index_or_path: /dev/video5, width: 640, height: 480, fps: 30}}" \
--task="Put lego brick into the transparent box" \ --task="Put lego brick into the transparent box" \
--duration=60 --duration=60
``` ```