Implementing a Pre-trained Deep Learning Model to Re-Style Images

by. Jongwon Lee | 191 Views (125 Uniq Views) | over 3 years ago
#OpenCV #ImageProcessing #Python #DeepLearning #AI
Explains how to use a pre-trained model to perform image processing.
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Why do we use it?


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import cv2
import numpy as np

net = cv2.dnn.readNetFromTorch('models/eccv16/starry_night.t7')

img = cv2.imread('imgs/01.jpg')

h, w, c = img.shape

img = cv2.resize(img, dsize=(500, int(h / w * 500)))

MEAN_VALUE = [103.939, 116.779, 123.680]
blob = cv2.dnn.blobFromImage(img, mean=MEAN_VALUE)

net.setInput(blob)
output = net.forward()

output = output.squeeze().transpose((1, 2, 0))

output += MEAN_VALUE
output = np.clip(output, 0, 255)
output = output.astype('uint8')

cv2.imshow('img', img)
cv2.imshow('result', output)
cv2.waitKey(0)