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An algorithm that uses YoloV5 and DeepSORT to count and measure the number of vehicles in a video stream, it detects the vehicles with YoloV5 and tracks them with DeepSORT to maintain a count of unique vehicles in the video. It also calculates the frames per second (FPS) of the video stream.

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mahimairaja/vechicle-counting-yolo

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Vehicle Counting using Yolov5 and Deep Sort

Status License

On CPU - 12 to 15 FPS

Pre-requisites :

  1. Clone the Repository vehicle-counting-yolov5
git clone https://github.com/mahimairaja/vehicle-counting-yolov5.git

cd vehicle-counting-yolov5
  1. Clone the legacy Yolo-v5 Repository
git clone https://github.com/ultralytics/yolov5.git
  1. Install the libraries
pip install -r requirements.txt

Directory Structure :

After completing the above steps your directory should look like somewhat as of below structure

  • vehicle-counting-yolov5
    • deep_sort
    • yolov5
    • input.mp4
    • yolov5s.pt
    • tracker.py
    • requirements.txt

Run the algorithm

python tracker.py 
# This will download model weight - yolov5s.pt to base folder on first execution.

Feel free to conect with me...

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An algorithm that uses YoloV5 and DeepSORT to count and measure the number of vehicles in a video stream, it detects the vehicles with YoloV5 and tracks them with DeepSORT to maintain a count of unique vehicles in the video. It also calculates the frames per second (FPS) of the video stream.

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