mirror of
https://github.com/opencv/opencv.git
synced 2024-11-27 20:50:25 +08:00
54 lines
1.8 KiB
Python
54 lines
1.8 KiB
Python
from __future__ import print_function
|
|
import cv2 as cv
|
|
import numpy as np
|
|
import argparse
|
|
|
|
parser = argparse.ArgumentParser(
|
|
description='This script is used to run style transfer models from '
|
|
'https://github.com/jcjohnson/fast-neural-style using OpenCV')
|
|
parser.add_argument('--input', help='Path to image or video. Skip to capture frames from camera')
|
|
parser.add_argument('--model', help='Path to .t7 model')
|
|
parser.add_argument('--width', default=-1, type=int, help='Resize input to specific width.')
|
|
parser.add_argument('--height', default=-1, type=int, help='Resize input to specific height.')
|
|
parser.add_argument('--median_filter', default=0, type=int, help='Kernel size of postprocessing blurring.')
|
|
args = parser.parse_args()
|
|
|
|
net = cv.dnn.readNetFromTorch(cv.samples.findFile(args.model))
|
|
net.setPreferableBackend(cv.dnn.DNN_BACKEND_OPENCV)
|
|
|
|
if args.input:
|
|
cap = cv.VideoCapture(args.input)
|
|
else:
|
|
cap = cv.VideoCapture(0)
|
|
|
|
cv.namedWindow('Styled image', cv.WINDOW_NORMAL)
|
|
while cv.waitKey(1) < 0:
|
|
hasFrame, frame = cap.read()
|
|
if not hasFrame:
|
|
cv.waitKey()
|
|
break
|
|
|
|
inWidth = args.width if args.width != -1 else frame.shape[1]
|
|
inHeight = args.height if args.height != -1 else frame.shape[0]
|
|
inp = cv.dnn.blobFromImage(frame, 1.0, (inWidth, inHeight),
|
|
(103.939, 116.779, 123.68), swapRB=False, crop=False)
|
|
|
|
net.setInput(inp)
|
|
out = net.forward()
|
|
|
|
out = out.reshape(3, out.shape[2], out.shape[3])
|
|
out[0] += 103.939
|
|
out[1] += 116.779
|
|
out[2] += 123.68
|
|
out /= 255
|
|
out = out.transpose(1, 2, 0)
|
|
|
|
t, _ = net.getPerfProfile()
|
|
freq = cv.getTickFrequency() / 1000
|
|
print(t / freq, 'ms')
|
|
|
|
if args.median_filter:
|
|
out = cv.medianBlur(out, args.median_filter)
|
|
|
|
cv.imshow('Styled image', out)
|