Welcome to the Automatic Pothole Detection project! This repository contains Python code designed to automatically detect potholes in user-submitted images. The system utilizes YOLO (You Only Look Once) for object detection and incorporates EXIF data for improved accuracy.

Detected potholes are visualized in an interactive web interface, and the results of predictions are stored in the runs/detect/predict folder. Images without detections are moved to the no_detection folder. These folders are all created automatically.

Explore the Detected Potholes Map - an interactive map of detected potholes.

• Python 3.6 or later
• Git

git clone https://github.com/your-username/your-repository.git
cd your-repository

python -m venv venv
source venv/bin/activate   # On Windows: venv\Scripts\activate
pip install -r requirements.txt

python predict.py

1. Ensure your images are in the prediction_images folder.
2. Predictions will be saved in the runs/detect/predict folder.
3. Images without detections will be moved to the no_detection folder.
4. Verify that your images have EXIF data, including GPS information for accurate predictions.

# Note: Only run automation.py if your images contain EXIF data
python automation.py

• This script generates an interactive map named detected.html showcasing the locations of detected potholes.

• Ensure GPS data is available in the images for accurate mapping.

• predict.py: Python script for predicting potholes using YOLO and processing images.

• automation.py: Python script for generating an interactive map of detected potholes.

• GPS_extraction.py: Dependency for extracting GPS location from images.

• prediction_images/: Folder containing images for prediction.

• train_runs/: Folder containing YOLO training runs.

• runs/: Folder for storing detection results.

  • detect/: Subfolder for detection results.
    • predict/: Subfolder for predicted images.

• no_detection/: Folder for images with no detected potholes.

Explore the Detected Potholes Map - an interactive map of detected potholes.

Contributions are welcome! If you'd like to contribute to the development of this project, please open an issue or submit a pull request.