Closed eberrigan closed 5 months ago
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Files that changed from the base of the PR and between f0f8462567dd3ba9c86dd5c740eb8074b8683764 and 1960cf85b789dfd3d6ca46e182ef862672a0aa06.
The changes made across various files aim to enhance compatibility, update dependencies, and refine functionality. These adjustments include modifying dependencies, updating version constraints, and refining scripts to address potential issues and improve the overall build and runtime environment.
Files | Change Summary |
---|---|
.conda/bld.bat , .conda/build.sh |
Removed --no-binary option for qudida,albumentations in pip install command. |
.conda/meta.yaml , pypi_requirements.txt ,.conda_mac/meta.yaml |
Added qudida , albumentations , ndx-pose ; updated version constraints; adjusted build number. |
requirements.txt |
Updated versions; removed ndx-pose , albumentations ; added tensorflow-hub for specific platforms. |
sleap/nn/data/augmentation.py ,tests/nn/data/test_augmentation.py |
Modified uniform_noise function; added tests for AlbumentationsAugmenter. |
environment.yml , environment_no_cuda.yml |
Updated tensorflow version constraint. |
sleap/version.py |
Updated version number from "1.3.3" to "1.4.0". |
.github/workflows/build.yml ,.github/workflows/ci.yml |
Updated macOS version in matrix configuration. |
environment_mac.yml |
Added importlib-metadata ; updated networkx ; commented out tensorflow-hub . |
.conda/condarc.yaml |
Added a commented-out channel link for sleap . |
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All modified and coverable lines are covered by tests :white_check_mark:
Project coverage is 73.31%. Comparing base (
bc69dd0
) to head (1960cf8
).
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Description
Notes:
sleap/label/dev
until the new TensorFlow v2.7.0 package is moved over tomain
(this will break v1.3.3 installs)Types of changes
Does this address any currently open issues?
1721
Outside contributors checklist
Thank you for contributing to SLEAP!
:heart:
Summary by CodeRabbit
qudida
,albumentations
, andndx-pose
to enhance functionality.opencv-python
,tensorflow
, and others to ensure compatibility and performance.uniform_noise
function and adding relevant tests.