comma10k VS autoware

Comma pencil is still a thing that needs lots of help. https://github.com/commaai/comma10k Also, sure read the OpenPilot code, find bugs or improvements and submit useful PRs.

The modern successor is https://github.com/commaai/comma10k

You can see the raw data that Comma is using for both cameras here: https://github.com/commaai/comma10k/tree/master/imgs2

TRY A TWO! https://comma.ai/compare Help with comma pencil! https://github.com/commaai/comma10k

There's also comma10k, which is actually more in the spirit of open source relying on open collaboration. https://github.com/commaai/comma10k

Openpilot is not fully end to end to yet. The longitudinal policy is still done classically, which requires explicit lead car detection. And by default the lateral does explicit lane line detection to keep itself centered with a hand coded planer. I can't comment on exactly how it's done since my understand of machine learning is purely superficial, but the model is also trained to detect lane lines and lead cars using a segnet based on this comma10k dataset, which has hand labeled images. Sky isn't one of these labels though.

This is great for projects where management or tracking of some sort is done from a public Google spreadsheet. Here's some examples where I've put it to use.

Here's a project where I sent in a PR that was merged to display annotation progress:

https://github.com/commaai/comma10k/pull/2767

Here's a wiki entry using it to display the current number of bounty contributors and bounty amount ($8K+!):

https://github.com/commaai/openpilot/wiki/Toyota-Lexus#2021-...

If you're organizing something for your community using a spreadsheet, maybe consider using Cell Shield to put a little badge somewhere visible.

Our goal is to use active learning to use a COCO pre-trained model and fine-tune it on a dataset for autonomous driving. For this transfer task, we are using the Comma10k dataset. From the repository: "It's 10,000 PNGs of real driving captured from the comma fleet. It's MIT license, no academic-only restrictions or anything."

Not a book/course recommendation. If you have already gone through the official wiki and if you're good with C++, I would suggest looking at Autoware.Auto (ROS2) or Autoware.AI(ROS1, if you're into it) for a deep dive. It's a FOSS Autonomous Driving Platform that's actively used by OEMs in their own development. IMO, their code should give you the best exposure on how to use ROS in the most efficient way possible. Just remember to keep the ROS API documentation open in the background for reference.

https://github.com/autowarefoundation/autoware for autonomous cars

Autoware is a much more professional, friendly community https://github.com/autowarefoundation/autoware