Add docker-compose support for easier and more portable environment set-up

[apockill]

What this does

This PR enables users to easily build and enter a docker container which has lerobot and it's dependencies installed.

Installing lerobot is now as easy as:

docker compose build
docker compose run lerobot

and that plops you right into a container within a tested lerobot environment.

Features:

• It mounts the current directory at runtime, so development is exactly the same as local development
• It mounts "/dev/" allowing serial communication as though you were running it as host
• It will help linux users who are suffering from environment issues. More on this below.
• It opens up ports that are used within the lerobot scripts (like visualize_dataset and visualize_dataset_html)
• Wandb credentials are mounted into the container

Why:

• I'm using ubuntu 22.04 and have been frustrated several times debugging different dependency related issues. For example, the control_robot record functionality expects that I will want to save my video using libsvtav1 (see video_utils.encode_video_frames). However, for whatever reason my version of ffmpeg doesn't allow that, and I had to manually edit code to get off the ground.
• There are currently incompatibilities with dependencies and their build version. For example, I ran into this issue: Torchvision import leads to OpenCV imshow freeze pytorch/vision#5940
  Which froze my development, since I wanted to run imshow and check out the cameras when debugging policies.

Anyways, I think it'd be exciting to give users another way to install dependencies.

I don't want to get too far into this without some buy-in. Please let me know if this is interesting, and would be wanted. Cheers!

How it was tested

If folks agree this is desired, I'll add a CI pipeline that validates the build.

Personally, I'm still working on testing this. I'll report back after feedback from reviewers.

Here's what I've personally tested, so far:

• visualize_dataset: Works, but you need the rerun server locally. I forward the ports in the docker-compose.
• visualize_dataset_html.py: Works great
• control_robot, train, and replay
• Run unit tests
• Validate cv2.imshow works
• Wandb credential passthrough works
• Huggingface credential passthrough works
• Anything else I'm missing? Let me know! 😁

How to checkout & try? (for the reviewer)

Just go ahead and check out my fork, and run the commands I documented in the README. I'm most interested in tests done in different hardware. I was thinking of supporting GPU and CPU cases, but is it worth supporting ARM images (a la Jetson) as well?

TODO:

• Fix cv2.imshow crashing if torchvision has been installed
• Record, train, test a policy as a sanity test
• Split docker-compose into multiple 'services', to allow users to docker run lerobot-gpu or 'docker run lerobot-cpu'. It might "just work" already on cpu machines, I'll test that later. It would be easier to maintain just one Dockerfile.

[apockill]

Most of this build is identical to docker/lerobot-gpu-dev, except:

• added the poetry install step and POETRY_EXTRAS env variable, using buildkit caching
• added poetry as the ENTRYPOINT