Skip to content

nanamiwang/comma10k

 
 

Repository files navigation

comma10k

Completion Progress Badge

We are releasing the first 1,000 images of our internal comma10k dataset. After we clean up these labels, we'll release more. Learn more from the Medium post, or on the comma.ai discord in the #comma-pencil channel.

Alt

It's 1,000 pngs of real driving captured from the comma fleet. It's MIT license, no academic only restrictions or anything. It also includes our internal segnet's guess at category.

Run

./viewer.py
to see them with segnet overlay.

Directories

 imgs/  -- The png image files
 masks/ -- PNG segmentation masks (update these!)
 segs/  -- The outputs in probablity from our internal segnet (unreleased, too big)

Categories of internal segnet

 0 - #000000 - empty
 1 -         - sky (deprecated, now undrivable)
 2 - #402020 - road (all parts, anywhere nobody would look at you funny for driving)
 3 - #ff0000 - lane markings (don't include non lane markings like turn arrows and crosswalks)
 4 - #808060 - undrivable
 5 - #00ff66 - movable (split into vehicles and people/animals?, actually don't)
 6 -         - signs and traffic lights (deprecated, now undrivable)
 7 - #cc00ff - my car (and anything inside it, including wires, mounts, etc...)

How can I help?

Start labelling!

Useful label tools:

  • The included comma pencil tool
  • img-labeler
  • An external image manipulation tool such as GIMP (Free) or Adobe Photoshop (Paid) If you choose to use an external tool please ensure your color mode is set to 8-bit, and that antialiasing doesn't change the colors on the edges of your mask.
  1. Visit the #comma-pencil channel on the comma.ai Discord for the latest news and chat about the project.
  2. Visit the Google Spreadsheet and identify images that haven't been claimed or completed.
  3. Create an Issue on this repository to indicate which images you intend to label. This is to ensure we don't have two people working on one at the same time, which would be a waste of time.
  4. Fork this repository to your account using the "Fork" button in the top right
  5. Clone your fork, and use your labelling tool of choice to label some images
  6. Open a pull request to the official repository to submit your changes!

Beginner Tutorial

Using the comma pencil tool (only works with MacOS/Linux)

See the pencil folder.

cd pencil
pip install -r requirements.txt
python server.py

Then open a browser window to http://localhost:5000/

The Goal

Alt

About

10k images for training segnets

Resources

License

Stars

Watchers

Forks

Packages

 
 
 

Languages

  • Scheme 74.6%
  • Python 13.6%
  • JavaScript 4.9%
  • HTML 4.6%
  • Shell 1.2%
  • CSS 1.1%