j-a-i-a-n-a-n-d/Vehicle-Counting-Using-YOLO-COCO

yolo vehicle counter based on coco dataset

Vehicle Counting Application using YOLOv3

YOLO (You Only Look Once)

You Only Look Once (YOLO) is a CNN architecture for performing real-time object detection. The algorithm applies a single neural network to the full image, and then divides the image into regions and predicts bounding boxes and probabilities for each region

Requirements for running the project

• python (>=3.6)

• openCV (Stable version)

• imutils

• sciPY

• numPY

• weights file for the coco dataset

https://pjreddie.com/media/files/yolov3.weights

Runnning the Application

python yolo_video.py --input inputVideos/highway.mp4 --output outputVideos/highwayOut.avi --yolo yolo-coco

python yolo_video.py --input inputVideos/highway.mp4 --output outputVideos/highwayOut.avi --yolo yolo-coco --confidence 0.3

Resources

• https://medium.com/analytics-vidhya/object-detection-using-yolov3-d48100de2ebb

• https://opencv-tutorial.readthedocs.io/en/latest/yolo/yolo.html

• https://www.analyticsvidhya.com/blog/2021/06/implementation-of-yolov3-simplified/

For Running Cuda as a Backend

• https://medium.com/geekculture/setup-opencv-dnn-module-with-cuda-backend-support-for-windows-7f1856691da3
• https://techzizou.com/setup-opencv-dnn-cuda-module-for-linux/