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Object-detection annotations for the scene in the COCO JSON format — images, categories, and per-object bounding boxes as [x, y, width, height]. Grouped with YOLO and Pascal-VOC twins for testing annotation-format conversion.
The same detection boxes in the Pascal VOC XML format — a per-image annotation with size, and one object element per box with pixel corner coordinates. The XML twin of the COCO and YOLO annotations.
COCO JSON with bounding boxes and polygon segmentation for the retail scene.
YOLO-format normalised boxes for the retail detection scene.
COCO JSON with bounding boxes and polygon segmentation for the warehouse scene.
Pascal VOC XML annotations for the warehouse detection scene.
YOLO-format normalised boxes for the warehouse detection scene.
The same detection boxes in the YOLO text format — one object per line as class id and box centre, width, and height normalised to 0–1. The format twin of the COCO and VOC annotations.
The class-name list for the detection scene, one label per line — index equals the zero-based line number, matching the YOLO class ids. A companion to the COCO/YOLO/VOC annotation files.
Synthetic mAP evaluation summary for object-detection benchmark harness tests.
Sample keypoint annotations (visible/occluded flags) for pose-estimation loader tests.
Synthetic aerial detection scene with 2 labelled objects at known coordinates.
Synthetic retail detection scene with 3 labelled objects at known coordinates.
Synthetic warehouse detection scene with 3 labelled objects at known coordinates.
ID list and model metadata for the Wave F embedding set.
Tiny 2×2 cosine similarity matrix for embedding eval unit tests.
Minimal SAMPLE eval metric JSON (accuracy) for dashboard parsers.
Minimal SAMPLE eval metric JSON (bleu) for dashboard parsers.
Minimal SAMPLE eval metric JSON (f1) for dashboard parsers.
Minimal SAMPLE eval metric JSON (latency_ms) for dashboard parsers.
Minimal SAMPLE eval metric JSON (toxicity) for dashboard parsers.
Combined class-name list for Wave F warehouse, retail, and aerial detection scenes.
An extractive question-answering dataset in the SQuAD v2.0 JSON structure — titled articles with context paragraphs, questions, character-offset answers, and one deliberately unanswerable question. Synthetic content; a fixture for QA model training and SQuAD-format loaders.
Failed tool invocation rows for agent error-handling and retry tests.
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