Akilarasan01/car-parts-and-damage-dataset

Car Parts and Damages Polygon Dataset

Dataset Summary

The Car Parts and Damages Polygon Dataset consists of 1,812 high-resolution images, each annotated with polygon-based segmentation masks for either car parts or car damages. The dataset is designed to support training and evaluation of deep learning models for fine-grained object detection, instance segmentation, and automotive inspection tasks.

✅ Key Stats:

• —Total images: 1,812
• —Car parts: 998 images
• —Car damages: 814 images
• —Total polygons: 24,851

This dataset supports advanced computer vision tasks such as automated damage detection, insurance assessment, vehicle inspection, and part localization.

Classes

🧩 Car Parts (998 Images)

Annotated polygon classes include:

• —Windshield
• —Back-windshield
• —Front-window
• —Back-window
• —Front-door
• —Back-door
• —Front-wheel
• —Back-wheel
• —Front-bumper
• —Back-bumper
• —Headlight
• —Tail-light
• —Hood
• —Trunk
• —License-plate
• —Mirror
• —Roof
• —Grille
• —Rocker-panel
• —Quarter-panel
• —Fender

💥 Car Damages (814 Images)

Annotated polygon classes include:

• —Dent
• —Cracked
• —Scratch
• —Flaking
• —Broken part
• —Paint chip
• —Missing part
• —Corrosion

Use Cases

This dataset is ideal for developing:

• —Instance segmentation models for automotive inspection
• —Damage classification and severity assessment tools
• —Insurance and repair estimate systems
• —Multi-class part detection and vehicle structure understanding

Dataset Format

• —Annotations are provided in polygon format, compatible with tools like COCO JSON or VIA/VGG annotations.
• —Each image is labeled with one of two categories: car parts or car damages, with corresponding polygon masks.