Python OpenCV "Canny" Edge Detection Tests. https://wsricardo.blogspot.com

artcam.py

"""
Created on Sat Jan  6 09:27:28 2024

@author: wsricardo
Blog: https://wsricardo.blogspot.com
"""

from PIL import Image
import cv2
import numpy as np
import random


def effect1( frame ):
    # Edges
    gray = cv2.cvtColor( frame , cv2.COLOR_BGR2GRAY )
    gray = cv2.medianBlur( gray, 5 )
    
    edges = cv2.adaptiveThreshold(
            gray ,
            255,
            cv2.ADAPTIVE_THRESH_MEAN_C,
            cv2.THRESH_BINARY, 9, 9
            )

    # Cartoonization
    color =cv2.bilateralFilter( frame, 9, 250, 250 )
    cartoon = cv2.bitwise_and( color, color, mask=edges )
    
    return cartoon 


def effect2( frame ):
    """
    Find edges
    """

    
    #mask = cv2.threshold(frame,
    #                    60, 255, 0)
    
    out = cv2.Canny( frame , 100, 250 )
    
    
    return cv2.addWeighted( 
        cv2.convertScaleAbs( 
            cv2.bitwise_not( out ), 
            alpha= 1.8, beta=10 ), 
        5., out, 0, 2.0 )

def effect3( frame ):
    
    frame = cv2.GaussianBlur(frame, (3, 5), sigmaX=0.5, sigmaY=0.7)
    frame = cv2.cvtColor( frame, cv2.COLOR_BGR2GRAY )
    
    
    
    #sobelx = cv2.Sobel( frame, ddepth=cv2.CV_64F, dx=1, dy=0, ksize=5 )
    #sobely = cv2.Sobel( frame, ddepth=cv2.CV_64F, dx=0, dy=1, ksize=5 )
    #frame = cv2.Canny( frame, 60, 130)
    
    #frame = cv2.Sobel( frame, ddepth=cv2.CV_64F, dx=1, dy=1, ksize=5 )
    
    ( thresh, frame ) = cv2.threshold( frame, 127, 255, cv2.THRESH_BINARY )
    
    #out = frame
    #frame = cv2.addWeighted( frame, 5.0, frame, 0.1, 5.0 ) 
    
    return cv2.bitwise_not(  frame )

def effect4( frame ):
    
    color = cv2.bilateralFilter( frame, 9, 250, 250 )
    
    frame = cv2.GaussianBlur(frame, (3, 5), sigmaX=0.5, sigmaY=0.7)
    frame = cv2.cvtColor( frame, cv2.COLOR_BGR2GRAY )
    
    frame = cv2.Laplacian( frame , 5,  cv2.CV_64F )
    
    frame = cv2.convertScaleAbs( frame, alpha=2.2, beta=10 )
    
    frame = cv2.addWeighted(frame, 5, frame, 0, 2.0)
    
    mask = cv2.adaptiveThreshold( frame , 255, cv2.ADAPTIVE_THRESH_MEAN_C, cv2.THRESH_BINARY, 5, 5 )
    
    return cv2.bitwise_not( cv2.bitwise_and( frame, frame,  mask=mask ) )


def effectCartoon( frame ):
    _ = None
    
    color = cv2.bilateralFilter( frame, 9, 250, 250 )
    frame = cv2.GaussianBlur( frame, (3,5), sigmaX= 0.5, sigmaY=0.7 )
    
    
    gray = cv2.cvtColor( color, cv2.COLOR_BGR2GRAY )
    ( ret, mask2 ) = cv2.threshold( gray, 80, 255, cv2.THRESH_BINARY )
    
    edges = cv2.Laplacian( gray, 5, cv2.CV_64F )
    edges = cv2.bitwise_not( edges )
    edges = cv2.convertScaleAbs( edges, alpha=2.8, beta=10 )
    edges = cv2.addWeighted( edges, 5, edges, 0, 2.0 )
    #edges = cv2.bitwise_not( edges )
    
    mask = cv2.adaptiveThreshold( edges , 255, cv2.ADAPTIVE_THRESH_MEAN_C, cv2.THRESH_BINARY, 5, 5)
    
    _ = cv2.bitwise_and( frame, frame, mask=mask )
    
    return  _

v = cv2.VideoCapture(0)
#v = cv2.VideoCapture("Rainy City Night - Royalty Free Stock Footage.mp4")
frame_width = int( v.get( 3 ) )
frame_height = int( v.get( 4 ) )

#out = cv2.VideoWriter( 'rainny-walking-footage.avi', cv2.VideoWriter_fourcc( 'M', 'J', 'P', 'G' ), 10, ( frame_width, frame_height ) )


while( True ):
    
    ret, frame = v.read()
    
    
    if ret == True:
        frame_cartoon  =  effectCartoon( frame )
        #out.write( frame )
        
        #cv2.imshow( "Cam", frame )
        cv2.imshow( "Cam Cartoon ", 
                   frame_cartoon )
    
    
        if cv2.waitKey( 1 ) & 0xFF == ord('q')  :
            break
        
    else:
        break
    

v.release()
#out.release()

cv2.destroyAllWindows()