petercorke / petercorke/machinevision-toolbox-python
Type-hint coverage audit: ~75% overall, parameter annotations lagging in several modules
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- Dominant language
- Python
- Stars
- 219
- Forks
- 30
- Avg merge
- 12d 23h
- Merged PRs (30d)
- 5
Description
Found 2026-08-10 while reviewing unmerged branches during a cleanup pass. An old typing branch (base commit 2022-10-18, predates the src/-layout restructure) attempted a broader typing pass but is no longer mergeable — its module paths no longer exist. Later, separate efforts did land on main (e.g. acc8222b, 524c7b8c, PR #32/fix/annotations-and-deprecation-warnings), so coverage today is real but partial, not complete.
An AST-based audit of parameter/return annotations across src/machinevisiontoolbox gives:
OVERALL: 54.3% params, 95.4% returns, 74.9% average
Return-type coverage is already strong almost everywhere (many modules at 100%); the gap is almost entirely on parameter annotations. Full per-module breakdown, sorted by average:
Module Param % Return % Avg %
cvfuncs.py 100.0% 0.0% 50.0%
ImageCore.py 30.9% 94.7% 62.8%
Sources.py 38.0% 91.1% 64.6%
ImageRegionFeatures.py 31.0% 100.0% 65.5%
BagOfWords.py 39.1% 95.7% 67.4%
ImageBlobs.py 38.0% 100.0% 69.0%
ImageConstants.py 72.3% 71.4% 71.9%
ImageMultiview.py 68.2% 83.3% 75.8%
ImageIO.py 58.5% 93.3% 75.9%
ImageWholeFeatures.py 55.6% 97.6% 76.6%
ImageProcessing.py 68.0% 86.4% 77.2%
ImagePointFeatures.py 55.6% 100.0% 77.8%
BundleAdjust.py 56.0% 100.0% 78.0%
VisualServo.py 63.2% 93.2% 78.2%
Kernel.py 57.5% 100.0% 78.8%
PointCloud.py 57.9% 100.0% 78.9%
Camera.py 61.3% 99.0% 80.1%
ImageColor.py 60.9% 100.0% 80.4%
ImageFiducials.py 69.6% 94.1% 81.9%
ImageLineFeatures.py 66.7% 100.0% 83.3%
ImageReshape.py 72.8% 96.0% 84.4%
ImageMorph.py 77.1% 100.0% 88.5%
ImageTensor.py 77.8% 100.0% 88.9%
ImageSpatial.py 78.7% 100.0% 89.4%
camera_derivatives.py 100.0% 100.0% 100.0%
decorators.py 100.0% 100.0% 100.0%
docbugs.py 100.0% 100.0% 100.0%
fiducial.py 100.0% 100.0% 100.0%
mvtb_types.py 100.0% 100.0% 100.0%
Fix
Work through the lowest-param-coverage modules first (cvfuncs.py, ImageCore.py, Sources.py, ImageRegionFeatures.py, BagOfWords.py, ImageBlobs.py — all under 40% param coverage), adding modern X | Y / X | None / list[X] annotations per the project's typing convention. No architectural changes needed, just incremental annotation additions per module.
Contributor guide
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First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start in src/machinevisiontoolbox/cvfuncs.py, ImageCore.py, Sources.py, ImageRegionFeatures.py, BagOfWords.py, and ImageBlobs.py, comparing their annotations with the project's existing typing convention and fully annotated modules such as mvtb_types.py. Add the missing parameter annotations using the stated modern forms while preserving behavior; done means the six lowest-coverage modules have been addressed.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- computer-vision
- Issue type
- Refactor
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Quiet
- Clarity
- Mostly clear
- Newbie friendliness
- 52/100