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  • 4 commits
  • 2 files changed
  • 2 contributors

Commits on May 26, 2026

  1. docs: clarify multi-class detectors require non-overlapping classes 

    Adds a prominent callout on the multi-choice answer-mode page and to the
create_multiclass_detector docstring explaining that multi-class detectors
return exactly one label per image and are not multi-label classifiers.
Users with overlapping classes are directed to use multiple binary detectors
instead.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
    @claude
    bwada and claude committed May 26, 2026
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  2. docs: tighten multi-class non-overlapping-classes copy 

    Editorial pass on the previous draft:
- Open with one direct sentence instead of two that restate the page title.
- Collapse the caution callout from three paragraphs to two; merge the
  "wrong tool" sentence into the rule-of-thumb so the same idea is not
  delivered twice.
- Replace "works best when" with "designed for" — the detector always
  returns a single label, so "best when" understates the constraint.
- Trade the person/vehicle example for the rule-of-thumb framing alone;
  avoids a context switch away from the dog-breed running example.
- In the docstring, swap the abstract co-occurrence wording for a concrete
  "Dog" / "Wearing collar" example.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
    @claude
    bwada and claude committed May 26, 2026
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  3. docs: address feedback on multi-class non-overlap guidance 

    - Recommend "a separate detector for each question you want to answer"
  rather than specifically a binary detector. The right mode follows from
  the question, so over-prescribing binary was wrong.
- Use "classes" instead of "categories" in the intro sentence to match the
  rest of the callout, the class_names parameter, and standard ML
  literature (scikit-learn, etc.).
- Swap the docstring co-occurrence example from a subject+attribute pair
  ("Dog" / "Wearing collar") to a paired-objects example ("a person and
  a dog") — the canonical multi-label intuition.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
    @claude
    bwada and claude committed May 26, 2026
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  4. docs: unify "belong to" for class membership across docs and docstring 

    The markdown said "each image should match exactly one" and the docstring
said "each image should fit exactly one" for the same idea. A reader
crossing between the docs site and the SDK reference would see drift.
Standardize on "belong to" — the precise class-membership term in ML
literature.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
    @claude
    bwada and claude committed May 26, 2026
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