james.maesandClaude Opus 4.7
3c5a171d34
Drops Apple's full YOLOv3 (~248 MB) into Sources/Resources/Models/ as the primary object detector. Xcode auto-compiles the .mlmodel into a .mlmodelc inside the app bundle; the model is a Vision-friendly pipeline so VNCoreMLRequest returns VNRecognizedObjectObservation directly — no manual NMS or output decoding required. Detection pipeline - YOLOv3 is the primary detector, returning bounding boxes labeled with COCO classes: person, bicycle, car, ..., bottle, wine glass, cup, fork, knife, spoon, bowl, ... laptop, mouse, remote, keyboard, cell phone, ... book, clock, vase. 80 classes total — covers the "is that a coffee mug" question and many others. - VNDetectFaceRectanglesRequest stays as a supplementary FACE labeler (more precise than YOLO's "person" for the face region). - VNRecognizeAnimalsRequest stays for finer-grained cat/dog labels. - Saliency and human-rectangle requests removed — YOLO supersedes them. - Per-label NMS with IoU>0.5 inside filterAndMerge drops same-label overlaps. Cross-label overlaps (e.g. person + face) are kept since they carry different information. - Min-confidence filter (Theme.Performance.detectionMinConfidence, 0.30) prunes weak guesses. Distribution - Model is tracked via Git LFS (.gitattributes) — it exceeds GitHub's 100 MB per-file limit. - README documents the `git lfs install && git lfs pull` prerequisite. - scripts/fetch-model.sh remains as a no-LFS fallback that downloads the same model from Apple's Core ML catalog. Theme knobs - Performance.detectionMinConfidence (default 0.30) - Performance.detectorModelName (default "YOLOv3") Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
12 lines
216 B
Plaintext
12 lines
216 B
Plaintext
.DS_Store
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build/
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DerivedData/
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.swiftpm/
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*.xcuserstate
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xcuserdata/
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# Regenerated from project.yml — do not commit
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VisionPOC.xcodeproj/
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# Models are stored via Git LFS (see .gitattributes). Nothing to ignore here.
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