fast_neural_style_transfer.py

model = cv2.dnn.readNetFromTorch('udnie.t7')

image = cv2.imread('yuvnish malhotra photo.jpg')

(h, w) = image.shape[:2]
image = cv2.resize(image, (600, h))
(h, w, c) = image.shape
print(h, w, c)

blob = cv2.dnn.blobFromImage(image, 1.0, (w, h), (103.939, 116.779, 123.680), swapRB=False, crop=False)

model.setInput(blob)
output = model.forward()
output = output.reshape((3, output.shape[2], output.shape[3]))
output[0] += 103.939
output[1] += 116.779
output[2] += 123.680
output /= 255.0
output = output.transpose(1, 2, 0)

image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
figure = plt.figure(figsize=(10, 10))
plt.imshow(image)
plt.axis('off')

figure2 = plt.figure(figsize=(10, 10))
plt.imshow(output)
plt.axis('off')