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。
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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
数据写入
| 内容 | 范围 | 说明 |
|---|---|---|
| genre | 0,1,2 | 0:左边单侧 1:右边单侧 2:双侧 |
| flagimg | 地址 | 贴图地址 |
| faceimg | 地址 | 人物正脸地址（脸要尽可能明显） |
| toflagimg | 地址 | 另外一侧贴图地址(右侧) |
In [5]
genre = 2 # 0:左边单侧 1:右边单侧 2:双侧flagimg = './agt.png' # 贴图地址faceimg = './p2c_photo.png' # 人物地址toflagimg = './bx.png' # 另外一侧贴图地址(右侧)
1.0、PaddleHub及PaddleGAN导入及函数定义
In [ ]
!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
In [ ]
import paddlehub as hubimport cv2import os face_landmark = hub.Module(name="face_landmark_localization") result = face_landmark.keypoint_detection(images=[cv2.imread(faceimg)])
In [9]
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.png')
im = cv2.imread(faceimg)
obj = cv2.imread('newflagimg.png')
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.jpg", mixed_clone)2.0 图像动漫化处理
In [10]
#生成动画头像from ppgan.apps import Photo2CartoonPredictor %cd /home/aistudio p2c = Photo2CartoonPredictor(output_path='/home/aistudio/result/') p2c.run(faceimg)
3.0 物品粘贴实现并展示
In [11]
if genre == 0:
sjb_hand(result, flagimg, './result/p2c_photo.png', 0)
os.rename("./inputimg.jpg", './newphoto.jpg')
sjb_hand(result, flagimg, './result/p2c_cartoon.png', 0)
os.rename("./inputimg.jpg", './newcartoon.jpg')elif genre == 1:
sjb_hand(result, flagimg, './result/p2c_photo.png', 1)
os.rename("./inputimg.jpg", './newphoto.jpg')
sjb_hand(result, flagimg, './result/p2c_cartoon.png', 1)
os.rename("./inputimg.jpg", './newcartoon.jpg')elif genre == 2:
tofaceimg = "inputimg.jpg"
sjb_hand(result, flagimg, './result/p2c_photo.png', 0)
sjb_hand(result, toflagimg, tofaceimg, 1)
os.rename("./inputimg.jpg", './newphoto.jpg')
sjb_hand(result, flagimg, './result/p2c_cartoon.png', 0)
sjb_hand(result, toflagimg, tofaceimg, 1)
os.rename("./inputimg.jpg", './newcartoon.jpg')from PIL import Image
Image.open('newcartoon.jpg')In [12]
from PIL import Image
Image.open('newphoto.jpg')
