A rendered detection scene annotated in COCO, YOLO, and Pascal-VOC formats — for testing annotation loaders, format converters, and vision pipelines against a known image.
Synthetic multi-class scene 1 (sky/ground/object/accent) for semantic-segmentation smoke tests. Paired with an indexed mask and class JSON.
Indexed L mask for scene 1: pixel value equals class id (1=sky, 2=ground, 3=object, 4=accent).
Class-id → label map for segmentation scene 1. Ground truth companion to the RGB and mask.
Synthetic multi-class scene 2 (sky/ground/object/accent) for semantic-segmentation smoke tests. Paired with an indexed mask and class JSON.
Indexed L mask for scene 2: pixel value equals class id (1=sky, 2=ground, 3=object, 4=accent).
Class-id → label map for segmentation scene 2. Ground truth companion to the RGB and mask.
Synthetic multi-class scene 3 (sky/ground/object/accent) for semantic-segmentation smoke tests. Paired with an indexed mask and class JSON.
Indexed L mask for scene 3: pixel value equals class id (1=sky, 2=ground, 3=object, 4=accent).
Class-id → label map for segmentation scene 3. Ground truth companion to the RGB and mask.
Synthetic multi-class scene 4 (sky/ground/object/accent) for semantic-segmentation smoke tests. Paired with an indexed mask and class JSON.
Indexed L mask for scene 4: pixel value equals class id (1=sky, 2=ground, 3=object, 4=accent).
Class-id → label map for segmentation scene 4. Ground truth companion to the RGB and mask.
Synthetic multi-class scene 5 (sky/ground/object/accent) for semantic-segmentation smoke tests. Paired with an indexed mask and class JSON.
Indexed L mask for scene 5: pixel value equals class id (1=sky, 2=ground, 3=object, 4=accent).
Class-id → label map for segmentation scene 5. Ground truth companion to the RGB and mask.
Synthetic multi-class scene 6 (sky/ground/object/accent) for semantic-segmentation smoke tests. Paired with an indexed mask and class JSON.
Indexed L mask for scene 6: pixel value equals class id (1=sky, 2=ground, 3=object, 4=accent).
Class-id → label map for segmentation scene 6. Ground truth companion to the RGB and mask.
Three-page TIFF of synthetic scenes — fixture for multipage TIFF loaders and page extractors.
RGBA sprite sheet (4×1 cells of 64px) with numbered frames for atlas / CSS-sprite tools.
RGBA sprite sheet (3×2 cells of 64px) with numbered frames for atlas / CSS-sprite tools.
RGBA sprite sheet (2×2 cells of 64px) with numbered frames for atlas / CSS-sprite tools.
Rendered SAMPLE data table as a PNG — for table-detection / OCR vision pipelines.
Rendered SAMPLE data table as a PNG — for table-detection / OCR vision pipelines.
Rendered SAMPLE data table as a PNG — for table-detection / OCR vision pipelines.
Compact sparkline PNG for chart-extraction / thumbnail vision tests.
Compact sparkline PNG for chart-extraction / thumbnail vision tests.
Compact sparkline PNG for chart-extraction / thumbnail vision tests.
Synthetic dashboard mock (KPI cards + bar chart) — SAMPLE UI for layout / chart vision models. Not a real product.
Synthetic dashboard mock (KPI cards + bar chart) — SAMPLE UI for layout / chart vision models. Not a real product.
Synthetic dashboard mock (KPI cards + bar chart) — SAMPLE UI for layout / chart vision models. Not a real product.
Synthetic dashboard mock (KPI cards + bar chart) — SAMPLE UI for layout / chart vision models. Not a real product.
Synthetic dashboard mock (KPI cards + bar chart) — SAMPLE UI for layout / chart vision models. Not a real product.
Synthetic dashboard mock (KPI cards + bar chart) — SAMPLE UI for layout / chart vision models. Not a real product.
Same fruit scene encoded as png — rung on the Wave E codec ladder for quality / convert comparisons.
Same fruit scene encoded as q20 — rung on the Wave E codec ladder for quality / convert comparisons.
Same fruit scene encoded as q50 — rung on the Wave E codec ladder for quality / convert comparisons.
Same fruit scene encoded as q80 — rung on the Wave E codec ladder for quality / convert comparisons.
Same fruit scene encoded as webp — rung on the Wave E codec ladder for quality / convert comparisons.
Same mug scene encoded as png — rung on the Wave E codec ladder for quality / convert comparisons.
Same mug scene encoded as q20 — rung on the Wave E codec ladder for quality / convert comparisons.
Same mug scene encoded as q50 — rung on the Wave E codec ladder for quality / convert comparisons.
Same mug scene encoded as q80 — rung on the Wave E codec ladder for quality / convert comparisons.
Same mug scene encoded as webp — rung on the Wave E codec ladder for quality / convert comparisons.
Same blocks scene encoded as png — rung on the Wave E codec ladder for quality / convert comparisons.
Same blocks scene encoded as q20 — rung on the Wave E codec ladder for quality / convert comparisons.
Same blocks scene encoded as q50 — rung on the Wave E codec ladder for quality / convert comparisons.
Same blocks scene encoded as q80 — rung on the Wave E codec ladder for quality / convert comparisons.
Same blocks scene encoded as webp — rung on the Wave E codec ladder for quality / convert comparisons.
Hard OCR case (skew): SAMPLE text rendered with challenging conditions. Pair with the .txt ground truth.
Hard OCR case (low-contrast): SAMPLE text rendered with challenging conditions. Pair with the .txt ground truth.
Hard OCR case (dotted): SAMPLE text rendered with challenging conditions. Pair with the .txt ground truth.
Hard OCR case (skew): SAMPLE text rendered with challenging conditions. Pair with the .txt ground truth.
Hard OCR case (low-contrast): SAMPLE text rendered with challenging conditions. Pair with the .txt ground truth.
Hard OCR case (dotted): SAMPLE text rendered with challenging conditions. Pair with the .txt ground truth.
Hard OCR case (skew): SAMPLE text rendered with challenging conditions. Pair with the .txt ground truth.
Hard OCR case (low-contrast): SAMPLE text rendered with challenging conditions. Pair with the .txt ground truth.
Soft-alpha cut-out (hair edges: hair-strands) for alpha-matting / background-removal quality tests.
Soft-alpha cut-out (hair edges: fine-fringe) for alpha-matting / background-removal quality tests.
Soft-alpha cut-out (soft edges: soft-edge-blob) for alpha-matting / background-removal quality tests.
Soft-alpha cut-out (hair edges: wispy-top) for alpha-matting / background-removal quality tests.
Soft-alpha cut-out (soft edges: plant-edge) for alpha-matting / background-removal quality tests.
Soft-alpha cut-out (hair edges: fur-edge) for alpha-matting / background-removal quality tests.
Soft-alpha cut-out (soft edges: glass-rim) for alpha-matting / background-removal quality tests.
A simple rendered street scene with a person, a car, and a tree at known pixel coordinates — the image the COCO, YOLO, and Pascal-VOC annotation twins describe. A fixture for testing object-detection loaders and annotation converters.
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.
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 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 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.
Six synthetic image-caption pairs in JSON Lines — for testing captioning loaders and vision-language eval harnesses.
Short VQA question/answer pairs referencing library images — a fixture for VQA loaders and eval scripts.
A synthetic RGB scene with three coloured shapes — input for semantic-segmentation models. Pair with the indexed mask twin.
Indexed 8-bit mask (0=background, 1–3=shapes) for the semantic-segmentation scene twin.
Class-id to name map for the semantic-segmentation mask (background + three shapes).
Synthetic warehouse detection scene with 3 labelled objects at known coordinates.
COCO JSON with bounding boxes and polygon segmentation for the warehouse scene.
YOLO-format normalised boxes for the warehouse detection scene.
Synthetic retail detection scene with 3 labelled objects at known coordinates.
COCO JSON with bounding boxes and polygon segmentation for the retail scene.
YOLO-format normalised boxes for the retail detection scene.
Synthetic aerial detection scene with 2 labelled objects at known coordinates.
COCO JSON with bounding boxes and polygon segmentation for the aerial scene.
Combined class-name list for Wave F warehouse, retail, and aerial detection scenes.
Sample keypoint annotations (visible/occluded flags) for pose-estimation loader tests.
EN image captions referencing Wave F detection scenes.
ES image captions referencing Wave F detection scenes.
FR image captions referencing Wave F detection scenes.
DE image captions referencing Wave F detection scenes.
JA image captions referencing Wave F detection scenes.
Parallel EN/ES/FR/DE captions per image for multilingual eval.
Manifest linking Wave F scene PNGs to per-language caption JSONL files.
Pascal VOC XML annotations for the warehouse detection scene.
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