---
dataset_info:
  features:
  - name: image_id
    dtype: int64
  - name: image
    dtype: image
  - name: width
    dtype: int32
  - name: height
    dtype: int32
  - name: objects
    struct:
    - name: id
      list: int64
    - name: area
      list: int64
    - name: bbox
      list:
        list: float32
        length: 4
    - name: category
      list:
        class_label:
          names:
            '0': Coverall
            '1': Face_Shield
            '2': Gloves
            '3': Goggles
            '4': Mask
  - name: detections
    list:
    - name: bbox
      list: int64
    - name: label
      dtype: string
    - name: sub_label
      dtype: string
    - name: alt_labels
      list: string
  - name: raw_response
    dtype: string
  - name: inference_info
    dtype: string
  splits:
  - name: test
    num_bytes: 3048948
    num_examples: 20
  download_size: 3042132
  dataset_size: 3048948
configs:
- config_name: default
  data_files:
  - split: test
    path: data/test-*
tags:
- hf-jobs
- object-detection
- uv-script
---

# Class-list detection with WeVisOne-VL

Boxes for `Coverall`, `Face_Shield`, `Gloves`, `Goggles`, `Mask` on `rishitdagli/cppe-5` (split `test`), from
[tencent/WeVisOne-VL-4B](https://huggingface.co/tencent/WeVisOne-VL-4B).
20 images, 20 with at least one detection,
130 detections. 14 boxes share their region with a box of another class (see `alt_labels`).

These are **zero-shot labels**: no human checked them. Treat them as a first pass for review.

## Columns added

- `detections`: list of `{bbox: [x1, y1, x2, y2], label, sub_label, alt_labels}`. `bbox` is in
  original-image pixels. `sub_label` is always empty (WeVisOne gives class labels only); it is
  there so the schema matches `qwen3vl-detect.py`. `alt_labels` lists other classes the model
  gave the same region (IoU >= 0.8); WeVisOne answers each class on its own,
  so one object can carry several class names.
- `raw_response`: the model's raw answer, for re-parsing.
- `inference_info`: JSON with the model, prompt, classes, image size and settings.

## Reproduction

Produced on [Hugging Face Jobs](https://huggingface.co/docs/huggingface_hub/guides/jobs) (`a10g-small`) with the [`wevisone-detect.py`](https://huggingface.co/datasets/uv-scripts/vlm-object-detection/raw/main/wevisone-detect.py) recipe from [uv-scripts](https://huggingface.co/uv-scripts). Run it yourself:

```bash
hf jobs uv run --flavor a10g-small https://huggingface.co/datasets/uv-scripts/vlm-object-detection/raw/main/wevisone-detect.py \
    rishitdagli/cppe-5 <output-dataset> --classes Coverall,Face_Shield,Gloves,Goggles,Mask --split test --max-samples 20 --shuffle --seed 42
```