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该内容介绍了基于PaddleHub人脸关键点检测的脸颊物品粘贴项目。先说明相关参数，接着阐述实现步骤：安装并导入PaddleHub及PaddleGAN，定义物品粘贴函数，进行图像动漫化处理，最后根据单侧或双侧需求实现物品粘贴并展示。还提及报错原因及解决方案。

基于PaddleHub人脸关键的检测的脸颊物品粘贴

效果展示

声明：以上均为展示，请不要上升到国家/球队/个人层面

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数据写入

genre = 2  # 0:左边单侧 1:右边单侧 2:双侧flagimg = './agt.webp'  # 贴图地址faceimg = './p2c_photo.webp'  # 人物地址toflagimg = './bx.webp'  # 另外一侧贴图地址(右侧)

1.0、PaddleHub及PaddleGAN导入及函数定义

!pip install -U paddlehub!hub install face_landmark_localization==1.0.2# 安装PaddleGAN的pip包，即可使用api预测方式!pip install --upgrade ppgan!pip install dlib==19.22.0 -i https://pypi.douban.com/simple

import paddlehub as hubimport cv2import osface_landmark = hub.Module(name="face_landmark_localization")result = face_landmark.keypoint_detection(images=[cv2.imread(faceimg)])

import numpy as npfrom PIL import Imageimport cv2import numpy as npfrom math import sqrtdef sjb_hand(result1, flagimg, faceimg, select):    result1 = result[0]['data'][0]    pts = []        def around(select):        order = [[2, 30, 3, 31], [30, 31, 16, 15]]        order = order[select]        for o in order:            tx = int(result1[o-1][0])            ty = int(result1[o-1][1])            pts.append([tx, ty])        x = []        y = []        for pt in pts:            x.append(pt[0])            y.append(pt[1])        # x = tuple(x)        # y = tuple(y)         x1 = min(x)        y1 = min(y)        x2 = max(x)        y2 = max(y)        # print(x1, x2, y1, y2)        return x1, x2, y1, y2        x1, x2, y1, y2 = around(select)    img = Image.open(flagimg)    # print(((x2 - x1) // 2), int((y2 - y1) * 1.2))    reim=img.resize((((x2 - x1) // 2), int((y2 - y1) * 1.2)))  # 宽*高    reim.save('newflagimg.webp')    im = cv2.imread(faceimg)    obj = cv2.imread('newflagimg.webp')    mask = 255 * np.ones(obj.shape, obj.dtype)    # print(im.shape, obj.shape)    center = (int(x1+(x2-x1)//2), y1+(y2-y1)//2)    mixed_clone = cv2.seamlessClone(obj, im, mask, center, cv2.  NORMAL_CLONE)    cv2.imwrite("inputimg.webp", mixed_clone)

2.0 图像动漫化处理

#生成动画头像from ppgan.apps import Photo2CartoonPredictor%cd /home/aistudiop2c = Photo2CartoonPredictor(output_path='/home/aistudio/result/')p2c.run(faceimg)

3.0 物品粘贴实现并展示

if genre == 0:    sjb_hand(result, flagimg, './result/p2c_photo.webp', 0)    os.rename("./inputimg.webp", './newphoto.webp')    sjb_hand(result, flagimg, './result/p2c_cartoon.webp', 0)    os.rename("./inputimg.webp", './newcartoon.webp')elif genre == 1:    sjb_hand(result, flagimg, './result/p2c_photo.webp', 1)    os.rename("./inputimg.webp", './newphoto.webp')    sjb_hand(result, flagimg, './result/p2c_cartoon.webp', 1)    os.rename("./inputimg.webp", './newcartoon.webp')elif genre == 2:    tofaceimg = "inputimg.webp"    sjb_hand(result, flagimg, './result/p2c_photo.webp', 0)    sjb_hand(result, toflagimg, tofaceimg, 1)    os.rename("./inputimg.webp", './newphoto.webp')    sjb_hand(result, flagimg, './result/p2c_cartoon.webp', 0)    sjb_hand(result, toflagimg, tofaceimg, 1)    os.rename("./inputimg.webp", './newcartoon.webp')from PIL import ImageImage.open('newcartoon.webp')

from PIL import ImageImage.open('newphoto.webp')

项目报错原因预测及解决方案

1、 dlib安装失败，请在GPU环境进行

2、项目失败，文件不存在。请查看是否添加图片并修改有关的地址链接

3、2.0动漫处理报错，原因极有可能是1中的安装失败或者图片脸部不够明显，建议更换GPU然后换图片

4、其他，可以留言进行询问，会第一时间回复