---
license: mit
language:
  - en
pipeline_tag: image-classification
tags:
  - computer-vision
  - accident-detection
  - yolov11
---
# Accident Classifier

## Model Description
This model classifies road-scene images into two categories: **accident** and **no_accident**. It is part of an academic AI-Based Road Accident Detection and Emergency Report Generation System.

## Intended Use
- Road-scene image classification for academic demonstrations.
- Supporting a prototype accident-analysis workflow.
- Educational experimentation with computer vision and deep learning.

## Model Details
- **Architecture:** YOLO11n classification model
- **Task:** Binary image classification
- **Classes:** `accident`, `no_accident`
- **Framework:** Python, Ultralytics, PyTorch

## Evaluation
- **Test accuracy:** 98.12%
- **Test images:** 1,858

Results are based on the project's current held-out test dataset. Performance on new, real-world images may differ.

## Limitations and Safety
This model is an academic prototype, not a verified emergency-response system. It may misclassify images and must not be used as the sole basis for emergency decisions. Predictions should be reviewed by a human. It does not automatically contact emergency services.

## Related Project
The model is used in the [AI-Based Road Accident Detection & Emergency Report Generation System](https://github.com/akashakash920692-byte/AI-Accident-Detection-System).