Datasets:
metadata
language:
- en
pretty_name: Wardy Hazard Object Detection Dataset
task_categories:
- object-detection
tags:
- yolo
- object-detection
- hazard-detection
- safety
- wardy
Wardy Hazard Object Detection Dataset
This dataset was prepared for training and evaluating indoor hazard object detection models. It contains images and YOLO-format bounding-box annotations.
Classes
| ID | Class |
|---|---|
| 0 | scissors |
| 1 | knife |
| 2 | cutter |
| 3 | syringe |
Versions
| Revision | Description |
|---|---|
hazard-objects-v1 |
Initial hazard object dataset |
hazard-objects-v2 |
Updated and extended hazard object dataset |
finetuning-v2 |
Additional fine-tuning dataset |
Use a revision tag instead of main when reproducibility is important.
Dataset Structure
The hazard-objects-v1 and hazard-objects-v2 archives use the following YOLO dataset structure:
dataset/
|-- data.yaml
|-- images/
| |-- train/
| |-- val/
| `-- test/
`-- labels/
|-- train/
|-- val/
`-- test/
Each annotation line follows the YOLO format:
class_id x_center y_center width height
Coordinates are normalized to values between 0 and 1.
Download with hf CLI
hf download chocochip119/hazard \
--type dataset \
--revision hazard-objects-v2 \
--local-dir ./hazard-dataset
Download with Python
from huggingface_hub import hf_hub_download
from zipfile import ZipFile
zip_path = hf_hub_download(
repo_id="chocochip119/hazard",
repo_type="dataset",
filename="dataset.zip",
revision="hazard-objects-v2",
)
with ZipFile(zip_path) as archive:
archive.extractall("./hazard_objects_v2")
Training with Ultralytics
After extracting the archive, update the path field in data.yaml for your environment.
from ultralytics import YOLO
model = YOLO("yolo11n.pt")
model.train(
data="./hazard_objects_v2/data.yaml",
epochs=100,
imgsz=640,
)
Limitations
- Class distributions may be imbalanced.
- Incorrect or missing annotations may exist.
- The dataset may not represent every environment, lighting condition, or camera angle.
- Models trained on this dataset require separate validation before real-world deployment.
- Safety-critical decisions must not rely only on predictions from a model trained with this dataset.
Source and License
The complete source and redistribution terms of all images have not yet been documented. Verify ownership, consent, privacy requirements, and licensing before using or redistributing this dataset.