Datasets:

moondream
/

car_part_damage

license: unknown
language:
  - en
pretty_name: Car Part Damage (Parts)
size_categories:
  - 1K<n<10K
task_categories:
  - image-segmentation
  - object-detection
tags:
  - car
  - car-parts
  - supervised

Car Part Damage (Parts)

Data format

Each example contains:

image: RGB image (Hugging Face Image feature; embedded so the viewer works)
image_id: original filename
width: image width in pixels
height: image height in pixels
annotations: list of detection objects (COCO-like), each with:
- id: integer object id from the annotation file
- category: car part label (string)
- bbox: [x_min, y_min, x_max, y_max] in absolute pixel coordinates (xyxy)
- segmentation: list of polygons, each polygon is a flat list [x1, y1, x2, y2, ...] in pixel coordinates. segmentation[0] is the exterior polygon; subsequent entries are holes if present.

Bounding boxes are derived from the exterior polygon by taking min/max of x and y.

Splits

train: 948 images
test: 50 images

Labels

The part classes are: Back-bumper, Back-door, Back-wheel, Back-window, Back-windshield, Fender, Front-bumper, Front-door, Front-wheel, Front-window, Grille, Headlight, Hood, License-plate, Mirror, Quarter-panel, Rocker-panel, Roof, Tail-light, Trunk, Windshield.

Usage

from datasets import load_dataset

ds = load_dataset("moondream/car_part_damage", split="train")
print(ds[0]["annotations"][0]["bbox"])  # [x_min, y_min, x_max, y_max]
print(ds[0]["annotations"][0]["category"])  # part name