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【作品展示】

 

【作品介绍】

用自已的照片来改造吧！

提示：要用一个t7，一个jpg哦

 

【作品源代码】

import cv2
import numpy as np


def computeMean(imagest): 
    b,g,r = cv2.split(imagest)
    b_mean = np.mean(b)
    g_mean = np.mean(g)
    r_mean = np.mean(r)
    mean = (b_mean, g_mean, r_mean)
    return mean


def inputImg(net, image, imagest, n):
    height = image.shape[0]
    width = image.shape[1]
    mean = computeMean(imagest)
    blob = cv2.dnn.blobFromImage(image, scalefactor=n, size=(width, height), mean=mean)
    net.setInput(blob)


def outputImg(net, imagest):
    out = net.forward()
    out = out.reshape(3, out.shape[2], out.shape[3])
    mean = computeMean(imagest)
    out[0] += mean[0]
    out[1] += mean[1]
    out[2] += mean[2]
    out /= 255
    out = out.transpose(1, 2, 0)
    return out

def load_tools():
    import cv2
    print('成功导入库：cv2')
    import numpy as np
    print('成功导入库：numpy')

def load_model(name):
    print('导入预设模型')
    return name

def load_picture(name):
    print('导入图片：%s' % name)
    return name

def mix_with_cv2(model=False, picture=False, n=1):
    if not model:
        print('未输入模型')
        exit()
    elif not picture:
        print('未输入图片')
        exit()
    else:
        global out
        net = cv2.dnn.readNetFromTorch('models/%s' % model)
        image = cv2.imread(picture)
        imagest = cv2.imread('styles/' + model[:-2] + 'jpg')
        inputImg(net, image, imagest, n)
        out = outputImg(net,imagest)
    return True

def show(mp=False):
    cv2.imshow('Styled image', out)
    cv2.waitKey(0)


# 风格迁移测试
load_tools()
m = load_model('the_wave.t7')
p = load_picture('20220415094302.jpg')
r = mix_with_cv2(m, p, 5)
show(r)


# import turtle as t


# t.done()

 

【提示】

部分含有Python第三方库相关内容的作品，在海龟编辑器网页端无法运行哦！如遇到这种情况，可以打开下面的链接，下载海龟编辑器客户端：

https://python.codemao.cn