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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
```
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