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AD through warp
#12
Comments
Can we get tests in for these |
yeah sure, I'm in the process of making the new branch and creating a PR |
Ad though
Each step should correspond to at least one PR. You don't need to support everything in one PR, for example, Again, and again, do keep in mind, every non-trivial PR should have its associated test cases. If the PR is submitted without test cases, it requires the reviews to understand every detail of the code, which isn't always the case. Approval from reviewers doesn't mean the code is written correctly, it only means 1) the codes and implementation don't look suspicious and 2) the codes are written in a good style. Correctness is guaranteed by test cases and CI. PRs without high test coverage usually don't get high-quality review feedback because reviewers don't want to spend their time investigating something that can't be verified very quickly. There might be some misunderstanding here on our mentorship here, because everyone here contributes with their free time from ❤️, one of the golden rules (I said) in open source development is to save others' time. Submitting a good-to-review PR, opening a well-explained and reproducible issue, reducing unnecessary multi-rounds communications, are some practices of this rule. |
This issue is for tracking the progress of enabling AD through
ImageTransformations.warp
.author: @SomTambe
mentors: @DhairyaLGandhi @johnnychen94
Background
ImageTransformations.jl
implements a backward mode warp, which performs the exact operations as elaborated in #11 . The target would be to get the gradient with respect to the input warp matrixW
, and as a long term goal, also the input imageX
.Roadmap
_getindex
BSplines
andExtrapolations
.SMatrix
andSVector
.homography
struct.ImageTransformations.warp!
ImageTransformations.warp
function.The text was updated successfully, but these errors were encountered: