Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Edit to Visual Perception note #119

Merged
merged 2 commits into from
Oct 26, 2024
Merged
Changes from all commits
Commits
File filter

Filter by extension

Filter by extension

Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
2 changes: 1 addition & 1 deletion docs/course/visual_perception.md
Original file line number Diff line number Diff line change
Expand Up @@ -92,7 +92,7 @@ I_{(L+M+S)}
In this equation, \(I_L\), \(I_M\), and \(I_S\) represent the intensities received by the long, medium, and short cone cells, respectively. Opponent signals are represented by the differences between combinations of cone responses.


We could exercise on our understanding of trichromat sensation with LMS cones and the concept of color oppenency by vising the functions available in our toolkit, `odak`.
We could exercise on our understanding of trichromat sensation with LMS cones and the concept of color opponency by vising the functions available in our toolkit, `odak`.
The utility function we will review is [`odak.learn.perception.color_conversion.primaries_to_lms()`](https://github.com/kaanaksit/odak/blob/321760f2f2f3e2639301ecb32535cc801f53dd64/odak/learn/perception/color_conversion.py#L292) from [`odak.learn.perception`](../odak/learn_perception.md).
Let us use this test to demonstrate how we can obtain LMS sensation from the color primaries of an image.

Expand Down
Loading