---
pretty_name: WildGUI Screenshots (part16–19)
license: cc-by-nc-4.0
language:
- en
tags:
- gui-agents
- gui-grounding
- interaction-trajectories
- video2gui
- wildgui
- screenshots
- images
- web
- desktop
- mobile
size_categories:
- 1M<n<10M
---

# WildGUI Screenshots (part16–19)

This repository hosts the **screenshot images for `part16`–`part19`** of
**WildGUI**, the dataset introduced by Video2GUI. It extends the main release at
[`xwm/WildGUI`](https://huggingface.co/datasets/xwm/WildGUI), which already
contains all annotations plus the screenshots for `part1`–`part15`.

The two repositories are split as follows:

| Repository | Annotations | Screenshots |
|---|---|---|
| [`xwm/WildGUI`](https://huggingface.co/datasets/xwm/WildGUI) | **All** parts (JSONL) | `part1`–`part15` |
| `joker-112/WildGUI_Screenshots` (this repo) | — | `part16`–`part19` |

So the annotations for `part16`–`part19` live in `xwm/WildGUI`, while their
screenshot frames live here. To work with `part16`–`part19` you need both: the
trajectories from `xwm/WildGUI` tell you *what action happens and where*, and
each action points at one screenshot frame stored in this repo.

## File Layout

Screenshots are grouped by the same `partN` shards used for the annotations,
then packed into uncompressed tar archives (the frames are already
JPEG-compressed):

```text
screenshots/
  part16/
    wildgui_part16_images_000001.tar
    wildgui_part16_images_000002.tar
    ...
  part17/
    wildgui_part17_images_000001.tar
    ...
  part18/
    ...
  part19/
    ...
```

Each tar holds up to ~20,000 frames. Inside a tar, every frame is stored under a
per-video directory:

```text
{video_id}/screenshot_{MM_SS}.jpg
```

`{MM_SS}` is the action timestamp normalized to zero-padded
`minutes_seconds` (e.g. the annotation timestamp `"00:18"` →
`screenshot_00_18.jpg`).

## Linking an Annotation to its Screenshot

Each trajectory action in `xwm/WildGUI` (for `part16`–`part19`) maps to exactly
one frame in this repo. Given a record's `video_id` and an action's `timestamp`:

1. Take the `partN` matching the annotation shard (e.g. `wildgui_part17.jsonl` →
   `screenshots/part17/`).
2. Normalize the timestamp to `MM_SS`: timestamps like `"00:18"`, `"1:05"`, or a
   raw second count are converted to total `minutes_seconds`, each part
   zero-padded to two digits.
3. The frame is `{video_id}/screenshot_{MM_SS}.jpg`, found inside one of that
   part's `wildgui_part{N}_images_*.tar` shards.

```python
def timestamp_to_suffix(ts: str) -> str:
    """'00:18' -> '00_18', '1:05' -> '01_05', '78' -> '01_18'."""
    ts = str(ts).strip()
    if ":" in ts:
        total = 0
        for part in ts.split(":"):
            total = total * 60 + int(part)
    else:
        total = int(float(ts))
    minutes, seconds = divmod(total, 60)
    return f"{minutes:02d}_{seconds:02d}"

# For annotation record {"video_id": "tPPzO7wot9s", ...}
# and action {"timestamp": "00:18", ...}:
#   arcname = "tPPzO7wot9s/screenshot_00_18.jpg"
```

## Downloading

Download a single part with the `huggingface_hub` CLI:

```bash
hf download joker-112/WildGUI_Screenshots \
  --repo-type dataset \
  --include "screenshots/part16/*" \
  --local-dir ./wildgui_screenshots
```

Then unpack the tar shards (each expands into `{video_id}/screenshot_*.jpg`):

```bash
for t in ./wildgui_screenshots/screenshots/part16/*.tar; do
  tar -xf "$t" -C ./wildgui_frames
done
```

For streaming pipelines (e.g. WebDataset), each tar can also be read directly
without extracting to disk.

## Notes

- This repo covers **only** `part16`–`part19`. For `part1`–`part15` screenshots
  and for all annotations, use
  [`xwm/WildGUI`](https://huggingface.co/datasets/xwm/WildGUI).
- A small fraction of annotated frames may be missing from the packed shards
  (source frame unavailable at pack time); treat a missing
  `{video_id}/screenshot_{MM_SS}.jpg` as a skippable example rather than an
  error.
- Frames are derived automatically from tutorial videos and may contain noise.
  Validate for your own downstream training or evaluation setting.

## Intended Use

These screenshots are intended for research on GUI agents, GUI grounding, action
prediction, interaction trajectory modeling, and multimodal agent pretraining,
paired with the annotations in
[`xwm/WildGUI`](https://huggingface.co/datasets/xwm/WildGUI).

## Citation

If you use these screenshots, please cite the Video2GUI paper:

```bibtex
@misc{xiong2026video2gui,
  title = {Video2GUI: Synthesizing Large-Scale Interaction Trajectories for Generalized GUI Agent Pretraining},
  author = {Xiong, Weimin and Gu, Shuhao and Ye, Bowen and Yue, Zihao and Li, Lei and Song, Feifan and Li, Sujian and Tian, Hao},
  year = {2026},
  eprint = {2605.14747},
  archivePrefix = {arXiv},
  primaryClass = {cs.CL},
  doi = {10.48550/arXiv.2605.14747},
  url = {https://arxiv.org/abs/2605.14747}
}
```