• Andrew Jones

Creating a sketched video using OpenCV & Python


A very quick post, showing how to take a video and create a 'sketched' version of it using OpenCV.

I have used and modified code that was originally posted here, so credit to askaswiss.com.

I've taken their code and applied it to a video file, stacking the output so we can see how cool the sketch looks vs. the original!

Code below:

#################################################################

# import packages

#################################################################

import numpy as np

import cv2

#################################################################

# bring in video file

#################################################################

cap = cv2.VideoCapture("driving_dubai_clipped.mp4")

#################################################################

# loop through frames

#################################################################

while True:

ret, frame = cap.read()

# convert to sketch

img_gray = cv2.cvtColor(frame, cv2.COLOR_RGB2GRAY)

img_blur = cv2.GaussianBlur(img_gray, (21, 21), 0, 0)

img_blend = cv2.divide(img_gray, img_blur, scale=256)

img_blend = cv2.cvtColor(img_blend,cv2.COLOR_GRAY2BGR)

# stack original and sketch frames

dual_image = np.vstack((img_blend,frame))

# display the resulting frame

cv2.imshow('img_contour',dual_image)

if cv2.waitKey(1) & 0xFF == ord('q'):

break

# release capture

cap.release()

cv2.destroyAllWindows()

We only require numpy and cv2 for this project.

After importing the video file, we loop through the frames, firstly converting to greyscale then applying a Gaussian blur to reduce noise in the frame. We then blend the original greyscale frame and the blurred frame, and I force it back to 3 colour channels using cv2.COLOR_GRAY2BGR purely so I can stack it with the original colour frame.

We then use numpy's vstack function to put the frames together and then visualise them. The result is below...

#python #opencv

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