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I am using the following code to convert photo to a drawing:

import cv2
import numpy as np

img = cv2.imread("adventure.jpeg")

# 1) Edges
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
gray = cv2.medianBlur(gray, 5)
edges = cv2.adaptiveThreshold(gray, 255, cv2.ADAPTIVE_THRESH_MEAN_C, cv2.THRESH_BINARY, 9, 9)

# 2) Color
color = cv2.bilateralFilter(img, 9, 300, 300)

# 3) Cartoon
cartoon = cv2.bitwise_and(color, color, mask=edges)


cv2.imshow("Image", img)
cv2.imshow("Cartoon", cartoon)
cv2.imshow("color", color)
cv2.imshow("edges", edges)
cv2.waitKey(0)
cv2.destroyAllWindows()

the result is as follows: enter image description here

However I do not want the above result, what I want is this:

enter image description here

How do I do it using opencv / deep learning ?

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This problem is known as "style transfer", and deep learning can achieve some pretty amazing results.

Here's a fantastic GitHub repo with an easy-to-use implementation of neural style transfer (usage instructions). I think you'll have better luck using a pre-built model like this rather than training your own.

If you want to train your own, this repo might be a good starting point. It has a training script included, you'll just need a bunch of training images and a style image.

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