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A python project that does real-time vehicle detection using a trained car-cascade Model

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drakyanerlanggarizkiwardhana/Real-time-Vehicle-Dection-Python

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Hi guys, This repository consist of a source code of script to detect cars in a video/camera frame and then draw rectangaluar boxes around them.

The ML algorithms used for detecting cars and bounding boxes coordinates is a pretrained cascade model Haarcascade car.

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Where is the full article ?

The full article for this project is originally published on my blog with an article with title Real-time vehicle detection in python

Getting started

Firstly we have to clone the project repository or download the zip of project and then extract it.

git clone https://github.com/Kalebu/Real-time-Vehicle-Dection-Python
cd Real-time-Vehicle-Dection-Python
Real-time-Vehicle-Dection-Python ->

Dependencies

Now once we have the project repo in our local directory, now lets install the dependecies required to run our script

pip install opencv-python

Sample video

The sample video we used in this project is cars.mp4 which will come as you download or clone the repository, to load a different video with different filename, you might wanna change the source code a bit.

def Simulator():
    CarVideo = cv2.VideoCapture('cars.mp4') # change cars.mp4 to name of your vidoe
    while CarVideo.isOpened():
        ret, frame = CarVideo.read()
        controlkey = cv2.waitKey(1)
        if ret:        
            cars_frame = detect_cars(frame)
            cv2.imshow('frame', cars_frame)
        else:
            break
        if controlkey == ord('q'):
            break

    CarVideo.release()
    cv2.destroyAllWindows()

running our script

Now you can launch your scripts;

python app.py 

If you use the provided sample video, your script is going to look as shown in the picture below;

drawing

Issues ?

Are you facing any issue while trying to run the script, well then raise an issue and I will do my best fixing it as soon as I can

Credits

All the credits to kalebu