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Update readme for visualization & examples

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Simon Alibert 2024-05-04 21:02:35 +02:00
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@ -118,19 +118,19 @@ wandb login
### Visualize datasets ### Visualize datasets
Check out [examples](./examples) to see how you can import our dataset class, download the data from the Hugging Face hub and use our rendering utilities. You can easily visualize episode from a dataset by executing our script from the command line:
Or you can achieve the same result by executing our script from the command line:
```bash ```bash
python lerobot/scripts/visualize_dataset.py \ python lerobot/scripts/visualize_dataset.py \
env=pusht \ --repo-id lerobot/pusht \
hydra.run.dir=outputs/visualize_dataset/example --episode-index 0
# >>> ['outputs/visualize_dataset/example/episode_0.mp4']
``` ```
Check out [example 1](./examples/1_load_lerobot_dataset.py) to learn how you can import and use our dataset class and download the data from the Hugging Face hub.
### Evaluate a pretrained policy ### Evaluate a pretrained policy
Check out [examples](./examples) to see how you can load a pretrained policy from the Hugging Face hub, load up the corresponding environment and model, and run an evaluation. Check out [example 2](./examples/2_evaluate_pretrained_policy.py) to see how you can load a pretrained policy from Hugging Face hub, load up the corresponding environment and model, and run an evaluation.
Or you can achieve the same result by executing our script from the command line: Or you can achieve the same result by executing our script from the command line:
```bash ```bash
@ -153,7 +153,7 @@ See `python lerobot/scripts/eval.py --help` for more instructions.
### Train your own policy ### Train your own policy
Check out [examples](./examples) to see how you can start training a model on a dataset, which will be automatically downloaded if needed. Check out [example 3](./examples/3_train_policy.py) to see how you can start training a model on a dataset, which will be automatically downloaded if needed.
In general, you can use our training script to easily train any policy in any environment: In general, you can use our training script to easily train any policy in any environment:
```bash ```bash