mahimairaja / vechicle-counting-yolo

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.

Vehicle Counting using Yolov5 and Deep Sort

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

2. Clone the legacy Yolo-v5 Repository

git clone https://github.com/ultralytics/yolov5.git

4. 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...