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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",
)
```
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