Canny Edge Detection OpenCV Python With Source Code

Canny Edge Detection OpenCV Python With Source Code

The Canny Edge Detection OpenCV Python Code was developed using Python OpenCV, This Canny Edge Detector is a multi-step algorithm used to detect a wide range of edges in images. The Canny edge detector is arguably the most well known and the most used edge detector in all of computer vision and image processing.

A Canny Edge Detection uses a filter based on the derivative of a Gaussian in order to compute the intensity of the gradients. The Gaussian reduces the effect of noise present in the image.

In this Python OpenCV Project also includes a downloadable Python Project With Source Code for free, just find the downloadable source code below and click to start downloading.

What is OpenCV?

OpenCV (Open Source Computer Vision Library) is an open-source computer vision and machine learning software library. OpenCV was built to provide a common infrastructure for computer vision applications and to accelerate the use of machine perception in commercial products.

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To start executing Canny Edge Detection OpenCV Python With Source Code, make sure that you have installed Python 3.9 and PyCharm in your computer.

Canny Edge Detection OpenCV Python With Source Code : Steps on how to run the project

Time needed: 5 minutes

These are the steps on how to run Canny Edge Detection OpenCV Python With Source Code

  • Step 1: Download the given source code below.

    First, download the given source code below and unzip the source code.Canny Edge Detection OpenCV download source code

  • Step 2: Import the project to your PyCharm IDE.

    Next, import the source code you’ve download to your PyCharm IDE.
    Canny Edge Detection OpenCV open project

  • Step 3: Run the project.

    last, run the project with the command “py main.py”
    Canny Edge Detection OpenCV run project

Installed Libraries

import cv2 as cv
import numpy as np
from matplotlib import pyplot as plt

Complete Source Code

import cv2 as cv
import numpy as np
from matplotlib import pyplot as plt


def canny():
    '''
    The Canny edge detection algorithm is composed
                      of 5 steps:

    1. Noise Reduction
    2. Gradient Calculation
    3. Non-maximum Suppressions
    4. Double threshold
    5. Edge Tracking by Hysteresis
    '''
    img = cv.imread("./img/sunflower.jpg", 0)
    canny = cv.Canny(img, 150, 200)

    title = ["Original Image", "Canny"]
    images = [img, canny]

    for i in range(len(images)):
        plt.subplot(2, 2, i+1), plt.imshow(images[i], 'gray')
        plt.title(title[i])
        plt.xticks([]), plt.yticks([])

    plt.show()


if __name__ == '__main__':
    canny()

Output

Canny Edge Detection OpenCV Python Output
Canny Edge Detection OpenCV Python Output

Download Source Code below

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Summary

In this Python OpenCV Project With Source Code, we learned how to use image gradients, one of the most fundamental building blocks of computer vision and image processing, to create an edge detector.

Specifically, we focused on the Canny edge detector, the most well known and most used edge detector in the computer vision community.

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Inquiries

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