Tested code for for python > 3.9 and numpy >= 2.0 #864
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Use u7122029 pullrequest in upstream to fix failing tests
bugfix: cval is marked as depreciated but alternative is unused.
dep: opencv 4 introduces error in tests
….1; 27 failing tests remain
* Move test dependencies into setup.py * Delete unused `requirements.txt` * Restrict testing in ubuntu-latest and windows-latest to pre-build python versions * Restrict macos testing to version which comes with available wheels (mainly for scikit-image)
After trying back and forth I came to the conclusion that the target value is highly dependend on the seed value. With `seed=1` for `iaa.ElasticTransformation` a couple lines above I could push down `count_bad` to 0. This means that I can either use a different seed or relax the test condition. Since I probably cannot control the exact values of future generators, I decided to do the later.
… module and assumes existence of NDArray which was introduced in numpy 1.21
…ndle anymore. Directly return zero-sized arrays in arithmetic function since there is nothing to do.
…havior Until this point, the polygon drawing exhibited inconsistent behavior between left and right boundaries of polygons. This behavior was considered a bug and the behavior thus changed. The changed tests mirrored this behavior and therefore must adapt to the new (consistent) behavior of scikit-image.
Prior to scikit-image 0.19.0 transform.warp converted float16 images implicitly to float64 prior to the calculation. This has changed such that we need to convert the image to a supported floating point format ourselves.
ci: Decided not to support depreciated BatchLoader on Windows
Make repository numpy 2.0 ready: * fixing comparisons between different dtypes * modified test which relied on numpy overflow behavior * made sure that C-arrays are passed when needed to opencv * fixed bugs related to implicit output dtype changes
Support opencv4 in tests
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Hi,
I don't know whether I will regret this in the future, but I decided to port the repository to recent python (currently 3.12), numpy (2.0.2), and opencv-python (4.10). All provided tests are passing on Ubuntu, Mac, and windows.
To @aleju : I am happy to maintain the project with it's current function set and I am also interested in providing PyPi packages so that it can be easily installed via
pip. The question is how to push this forward. It would be nice, if I can become co-owner of this repository. A even better solution would be a new github organizationimgaugwhich also owns the documentation and thus be independent of a single account.This pull request would closed quite a lot of open issues: