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| license: cc-by-nc-4.0 | |
| task_categories: | |
| - image-to-text | |
| - visual-question-answering | |
| language: | |
| - en | |
| tags: | |
| - gui | |
| - gui-agent | |
| - ui-understanding | |
| - screenshot | |
| - visual-grounding | |
| pretty_name: UIPro SeeClick-Web | |
| size_categories: | |
| - 1M<n<10M | |
| # UIPro-SeeClickWeb-Data-v1 | |
| Part of the **UIPro** GUI-agent training suite (ICCV 2025). This repository packages the | |
| **SeeClick-Web** source into the unified UIPro instruction-tuning format, with coordinates | |
| normalized to a **[0, 1000]** grid. | |
| > Web element grounding and referring pairs derived from the SeeClick web corpus. | |
| ## Dataset at a glance | |
| | | | | |
| | :--- | :--- | | |
| | **Total samples** | 4,935,436 | | |
| | **Valid images** | 265,080 | | |
| | **Avg. samples / image** | 18.62 | | |
| | **Coordinate scale** | 0–1000 | | |
| | **Source dataset** | [SeeClick-Web](https://github.com/njucckevin/SeeClick) | | |
| ### Samples by task | |
| | Task | Count | | |
| | :--- | ---: | | |
| | ElemGnd | 2,467,718 | | |
| | ElemRef | 2,467,718 | | |
| ## Repository file structure | |
| | File | Description | | |
| | :--- | :--- | | |
| | `SeeClick-Web_ElemGnd_ElemRef_4935k.json` | The dataset: a JSON **list** of 4,935,436 sample objects (schema below). | | |
| | `SeeClick-Web_ElemGnd_ElemRef_4935k_sample.json` | A small preview slice of the same schema, for quick inspection without downloading everything. | | |
| | `SeeClick-Web_ElemGnd_ElemRef_4935k_images.zip` | All screenshots referenced by the `image` field, preserving the relative paths stored there. | | |
| | `SeeClick-Web_ElemGnd_ElemRef_4935k_info.json` | Full generation report — per-task counts, image statistics, invalid-element breakdown, and the exact processing config. | | |
| Unzip `SeeClick-Web_ElemGnd_ElemRef_4935k_images.zip` and each sample's `image` path resolves relative to the extraction root. | |
| ## Sample schema — every field explained | |
| Each element of the main JSON list is one training sample. This dataset's samples use the | |
| following fields: | |
| | Field | Meaning | | |
| | :--- | :--- | | |
| | `conversations` | The vision-language dialogue: a list of turns, each `{"from": "human"|"gpt", "value": ...}`. The **human** turn holds the instruction/question and contains the `<image>` placeholder marking where the screenshot is inserted; the **gpt** turn is the ground-truth answer. | | |
| | `elem_role` | Accessibility/DOM role of the target element (e.g. `text`, `link`, `button`), carried over from the SeeClick web annotations. | | |
| | `id` | Unique sample identifier, formatted `autogui_<dataset>_<task>_<n>`. The `<task>` segment (e.g. `intentgnd`, `textloc`, `ocr`, `elemgnd`, `elemref`) tells you which task the sample belongs to. | | |
| | `image` | Path to the screenshot **inside `_images.zip`**, relative to the archive root. Load the image by joining this path with your extraction directory. | | |
| | `task_attr` | The task's target attribute in plain form — for grounding tasks the referred element's text/instruction; for OCR/referring tasks the queried coordinate string. Useful for filtering or building custom prompts without parsing the conversation. | | |
| | `unnormalized_box` | Ground-truth bounding box in **original image pixels**, as `[x1, y1, x2, y2]` (top-left, bottom-right). Present when a box is available. Note: the answer in the `gpt` turn is **normalized to 0–1000**, while this field is the raw-pixel box — divide by width/height and multiply by 1000 to reconcile them. | | |
| | `url` | Source web page URL the screenshot was captured from. | | |
| > **Note:** Fields tied to a bounding box (e.g. `unnormalized_box`) are only present on samples | |
| > that have a box; point-only answers (e.g. some intent-grounding samples) may omit them. | |
| ### The `conversations` field in detail | |
| `conversations` is a list of turns that a vision-language model consumes directly: | |
| - Each turn is `{"from": "...", "value": "..."}`. | |
| - `from` is either **`human`** (the prompt) or **`gpt`** (the ground-truth response). | |
| - The token **`<image>`** inside a human turn marks where the screenshot is spliced into the | |
| prompt — replace it with the actual image when tokenizing. | |
| ### Coordinate system | |
| - Answers are **normalized to the `0–1000` range** relative to image width/height. | |
| - A **point** answer is formatted `(x,y)`; a **bounding box** answer is `(x1,y1,x2,y2)`. | |
| - Prompts ending in `(with point)` expect a point; `(with bbox)` expect a box. | |
| - `unnormalized_box`, when present, is the same box in **raw pixels** — combine it with `wxh` | |
| (or the image's true size) to convert between pixels and the normalized grid. | |
| ## Example | |
| ```json | |
| { | |
| "id": "autogui_SeeClick-Web_elemref_856936", | |
| "conversations": [ | |
| { | |
| "from": "human", | |
| "value": "<image>\nPlease generate a brief description for the element at (263,735) (with point)" | |
| }, | |
| { | |
| "from": "gpt", | |
| "value": "Morgans" | |
| } | |
| ], | |
| "image": "SeeClick-Web/a7f6db97dcb3c2c876da06bb0dbac625.png", | |
| "unnormalized_box": [ | |
| 484, | |
| 788, | |
| 526, | |
| 800 | |
| ], | |
| "task_attr": "(263,735)", | |
| "elem_role": "text", | |
| "url": "https://www.countrybrewer.com.au/pages/Our-History.html" | |
| } | |
| ``` | |
| ## Usage | |
| ```python | |
| import json, os, zipfile | |
| from PIL import Image | |
| from huggingface_hub import hf_hub_download | |
| repo = "HongxinLi/UIPro-SeeClickWeb-Data-v1" | |
| samples = json.load(open(hf_hub_download(repo, "SeeClick-Web_ElemGnd_ElemRef_4935k.json", repo_type="dataset"))) | |
| images_zip = hf_hub_download(repo, "SeeClick-Web_ElemGnd_ElemRef_4935k_images.zip", repo_type="dataset") | |
| with zipfile.ZipFile(images_zip) as zf: | |
| zf.extractall("images/") | |
| s = samples[0] | |
| print(s["conversations"]) | |
| img = Image.open(os.path.join("images", s["image"])) # screenshot for this sample | |
| print("image size:", img.size) | |
| ``` | |
| ## About UIPro | |
| UIPro is a generalist GUI agent trained on 20.6M understanding tasks across 13 task types, | |
| followed by agent continued fine-tuning. See the project repository for the full data | |
| pipeline, training recipes and evaluation scripts: | |
| **https://github.com/ZJULiHongxin/UIPro** | |
| ## License | |
| Released under **CC BY-NC 4.0** (non-commercial research use). The underlying screenshots and | |
| annotations remain subject to the terms of their original source, [SeeClick-Web](https://github.com/njucckevin/SeeClick). | |
| ## Citation | |
| ```bibtex | |
| @inproceedings{uipro2025, | |
| title = {UIPro: A Generalist GUI Agent}, | |
| author = {Li, Hongxin and others}, | |
| booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)}, | |
| year = {2025} | |
| } | |
| ``` | |