| --- |
| license: bsl-1.0 |
| pretty_name: Widget2Code Bench Data v2 |
| task_categories: |
| - image-to-text |
| tags: |
| - screenshot-to-code |
| - react |
| - jsx |
| - multimodal |
| --- |
| |
| # Widget2Code Bench Data v2 |
|
|
| Evaluation targets for Widget2Code, rebuilt so that the picture a person reviews is the picture a |
| model is trained on and scored against. |
|
|
| | directory | samples | contents | |
| | --- | ---: | --- | |
| | `train-v2/` | 1,822 | training screenshots and canonical metadata | |
| | `test-v2/` | 1,000 | evaluation screenshots and canonical metadata | |
|
|
| ```text |
| train-v2/image_0004/ |
| test-v2/image_0001/ |
| ├── image.png # RGB, no alpha channel |
| └── metadata.json |
| ``` |
|
|
| ## Why v2 exists |
|
|
| Every target in Widget2Code Data V4.1 is RGBA, and its readers disagreed about what that meant. |
| `PIL.Image.convert("RGB")` — used by the benchmark, by the training image loader, by the vLLM |
| inference path and by the conversation's own image pipeline — drops the alpha channel and keeps |
| whatever RGB is stored underneath. A browser composites instead. So a person reviewing a target |
| saw one picture while the model was trained and scored on another. |
|
|
| Usually the disagreement was a few antialiased corner pixels. In 61 targets the capture had left |
| a whole neighbouring widget under the mask, and the model was scored on reproducing content no |
| design contains. On those, the reference render — the best answer the source pool has — scored |
| SSIM `0.5532` against the stored target and `0.6990` against the flattened one, against a pool |
| mean of `0.7664`. |
|
|
| Every target here is RGB with no alpha, so the three readers now see the same pixels. |
|
|
| ## What changed from V4.1 `train/` and `test/` |
|
|
| 127 of 2,822 targets differ visibly; the rest differ only where antialiased edge pixels were |
| composited. |
|
|
| | change | targets | |
| | --- | ---: | |
| | hidden content covered by the flat background | 61 | |
| | cropped to the bounding box of non-transparent pixels | 108 | |
| | both | 42 | |
|
|
| The background is white because it was measured, not assumed: on the affected samples the |
| reference render scores `0.7163` against a white-flattened target, `0.6161` against the stored |
| one and `0.5557` against a black-flattened one. |
|
|
| A transparent margin is what the capture left around the widget, not part of the design, so it is |
| cropped away. An **opaque** white margin is kept — a pixel the capture recorded as opaque is part |
| of the design. 140 targets therefore still carry a white border. |
|
|
| ## metadata.json |
|
|
| ```jsonc |
| { |
| "id": "image_2052", |
| "split": "test-v2", |
| "sha256": "...", // of this image.png |
| "category": "tools", // null when not labelled |
| "has_chart": null, |
| "side_info": { // prompt-ready, derived from these pixels |
| "dims": [243, 293], |
| "ocr": "- `\"Hello, Hayat\"` at (19.8%, 8.5%) of widget, font-height ≈ 12.3% ...", |
| "palette": "Target widget palette (top-4, after AA-fringe consolidation): ..." |
| }, |
| "flattened_from": { |
| "split": "test", |
| "original_sha256": "...", |
| "stored_size": [434, 444], |
| "crop_box": [95, 76, 338, 369], // null when nothing was cropped |
| "transparent_fraction": 0.651254, |
| "hidden_colours": 1171, // distinct RGB values under the mask |
| "background": [255, 255, 255] |
| } |
| } |
| ``` |
|
|
| `side_info` was regenerated from the new pixels with the benchmark 1.2.0 CPU container, the same |
| generator that produced the V4.1 metadata — verified by reproducing V4.1's own `side_info` byte |
| for byte on all 1,822 of its train targets. CPU output is canonical; GPU OCR follows a different |
| numeric path. |
|
|
| The `eval` ground-truth feature cache carried by V4.1 is **not** included: it describes pixels |
| that changed. A benchmark that misses it recomputes those features, which is correct and slower. |
|
|
| ## Pairing with reference sources |
|
|
| The `sft-v4` reference pool in |
| [Widget2Code-Data-V4](https://huggingface.co/datasets/Djanghao/Widget2Code-Data-V4) hard-codes |
| each target's **stored** canvas in its root `width`/`height`, so 108 of those sources no longer |
| match these targets. Regenerate the references against `train-v2`/`test-v2` rather than pairing |
| the two directly. |
|
|
| ## Download |
|
|
| ```python |
| from huggingface_hub import snapshot_download |
| |
| snapshot_download( |
| repo_id="Djanghao/Widget2Code-Bench-Data", |
| repo_type="dataset", |
| local_dir="Widget2Code-Bench-Data", |
| ) |
| ``` |
|
|
