EagleEye

EagleEye is a Python script that tracks public cameras scraped from Insecam public camera directory to find a specified object using the YOLOv4 object detection model. The objects available in this model can be found here. EagleEye also utilizes multithreading to efficiently scan multiple camera streams concurrently.

Features

• Detects objects in public camera streams using the YOLOv4 object detection model.
• Utilizes multithreading for efficient scanning of multiple camera streams simultaneously.
• Provides information about the detected camera's IP address, geolocation, and confidence level.
• Allows limiting the search to a specific country.
• Supports opening detected camera streams in a web browser.

Installation

1. Clone the repository:

git clone https://github.com/your-username/EagleEye.git

2. Install the required dependencies:

pip install -r requirements.txt

3. Download yolov4.weights file 245 MB: yolov4.weights (Google-drive mirror yolov4.weights) and place it in the directory named YOLO.

Usage

usage: EagleEye.py [-h] [-n NUMBER] -o {person,bicycle,car,...}
                   [-w WORKERS] [-c COUNTRY]

EagleEye - A tool for scanning public security cameras

options:
  -h, --help            show this help message and exit
  -n NUMBER, --number NUMBER
                        Maximum number of cameras to scan (100 is the deafult value)
  -o {person,bicycle,car,...}
                        The object you are searching for (Please refer to YOLOv3 - Darknet/coco.names - for more information)
  -w WORKERS, --workers WORKERS
                        Limit the number of workers in the multiprocessing pool
  -c COUNTRY, --country COUNTRY
                        Filter the results by specifying a country

Demonstration

Configuration

• MIN_CONFIDENCE: The minimum confidence threshold for object detection (default: 0.6).
• OPTIMIZED_MAX_WORKERS: The default number of worker threads (set to the number of CPU cores minus one).
• REQUEST_TIMEOUT: The timeout for web requests in seconds (default: 10).
• USER_AGENT: The user agent string for web requests.

Contributing

Contributions are welcome! If you find any issues or have suggestions for improvements, please open an issue or submit a pull request.

License

EagleEye is released under the GPLv3 License.

Acknowledgments

Special thanks to:

• The YOLO object detection model and weights.
• The Insecam website for providing access to public camera streams.
• The pycountry library for country information.
• The tqdm library for progress bar visualization.