现在的美颜特效有多可怕(现在的美颜特效有多可怕视频)

现在的美颜特效有多可怕(现在的美颜特效有多可怕视频)

导语

现在每一次出门，女友就喜欢拍照！BUT 嫌弃我给拍的照片角度不对，采光不好.......

总之一大堆理由，啥时候让我拍照的水平能有美颜相机三分之一的效果就好！​

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果然都是锻炼出来的，至少现在我能看出来朋友圈哪些小姐姐批没批过照片。​

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​逃不掉​

​逃不掉啊，为了摆脱这种局面——

立马给女友写了一款简易版本的美颜相机给她偷偷地用！这样子就不担心被锤了。机智如我.jpg

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正文

环境安装：

dlib库的安装 本博客提供三种方法进行安装

T1方法：pip install dlib

此方法是需要在你安装cmake、Boost环境的计算机使用 T2方法：conda install -c menpo dlib=18.18

此方法适合那些已经安装好conda库的环境的计算机使用， T3方法：pip install dlib-19.8.1-cp36-cp36m-win_amd64.whl

dlib库的whl文件——dlib-19.7.0-cp36-cp36m-win_amd64.rar

dlib-19.3.1-cp35-cp35m-win_amd64.whl

​cv2库安装方法：

pip install opencv-python

人脸五官，坐标、进行高斯模糊处理等等。

# 五官

class Organ():

def __init__(self,img,img_hsv,temp_img,temp_hsv,landmarks,name,ksize=None):

self.img = img

self.img_hsv = img_hsv

self.landmarks = landmarks

self.name = name

self.get_rect()

self.shape = (int(self.bottom-self.top),int(self.right-self.left))

self.size = self.shape[0] * self.shape[1] * 3

self.move = int(np.sqrt(self.size/3)/20)

self.ksize = self.get_ksize()

self.patch_img,self.patch_hsv = self.get_patch(self.img),self.get_patch(self.img_hsv)

self.set_temp(temp_img,temp_hsv)

self.patch_mask = self.get_mask_relative()

# 获取定位方框

def get_rect(self):

y,x = self.landmarks[:,1],self.landmarks[:,0]

self.top,self.bottom,self.left,self.right = np.min(y),np.max(y),np.min(x),np.max(x)

# 获得ksize,高斯模糊处理的参数

def get_ksize(self,rate=15):

size = max([int(np.sqrt(self.size/3)/rate),1])

size = (size if size%2==1 else size+1)

return(size,size)

# 截取局部切片

def get_patch(self,img):

shape = img.shape

return img[np.max([self.top-self.move,0]): np.min([self.bottom+self.move,shape[0]]),np.max([self.left-self.move,0]): np.min([self.right+self.move,shape[1]])]

def set_temp(self,temp_hsv):

self.img_temp,self.hsv_temp = temp_img,temp_hsv

self.patch_img_temp,self.patch_hsv_temp = self.get_patch(self.img_temp),self.get_patch(self.hsv_temp)

# 确认

def confirm(self):

self.img[:],self.img_hsv[:] = self.img_temp[:],self.hsv_temp[:]

# 更新

def update_temp(self):

self.img_temp[:],self.hsv_temp[:] = self.img[:],self.img_hsv[:]

# 勾画凸多边形

def _draw_convex_hull(self,points,color):

points = cv2.convexHull(points)

cv2.fillConvexPoly(img,color=color)

# 获得局部相对坐标遮盖

def get_mask_relative(self,ksize=None):

if ksize == None:

ksize = self.ksize

landmarks_re = self.landmarks.copy()

landmarks_re[:,1] -= np.max([self.top-self.move,0])

landmarks_re[:,0] -= np.max([self.left-self.move,0])

mask = np.zeros(self.patch_img.shape[:2],dtype=np.float64)

self._draw_convex_hull(mask,landmarks_re,color=1)

mask = np.array([mask,mask,mask]).transpose((1,2,0))

mask = (cv2.GaussianBlur(mask,ksize,0) > 0) * 1.0

return cv2.GaussianBlur(mask,0)[:]

# 获得全局绝对坐标遮盖

def get_mask_abs(self,ksize=None):

if ksize == None:

ksize = self.ksize

mask = np.zeros(self.img.shape,dtype=np.float64)

patch = self.get_patch(mask)

patch[:] = self.patch_mask[:]

return mask

主要美颜效果进行的处理如下：

# 美白

def whitening(self,rate=0.15,confirm=True):

if confirm:

self.confirm()

self.patch_hsv[:,:,-1] = np.minimum(self.patch_hsv[:,-1]+self.patch_hsv[:,-1]*self.patch_mask[:,-1]*rate,255).astype('uint8')

self.img[:]=cv2.cvtColor(self.img_hsv,cv2.COLOR_HSV2BGR)[:]

self.update_temp()

else:

self.patch_hsv_temp[:] = cv2.cvtColor(self.patch_img_temp,cv2.COLOR_BGR2HSV)[:]

self.patch_hsv_temp[:,-1] = np.minimum(self.patch_hsv_temp[:,-1]+self.patch_hsv_temp[:,255).astype('uint8')

self.patch_img_temp[:] = cv2.cvtColor(self.patch_hsv_temp,cv2.COLOR_HSV2BGR)[:]

# 提升鲜艳度

def brightening(self,rate=0.3,confirm=True):

patch_mask = self.get_mask_relative((1,1))

if confirm:

self.confirm()

patch_new = self.patch_hsv[:,1]*patch_mask[:,1]*rate

patch_new = cv2.GaussianBlur(patch_new,(3,3),0)

self.patch_hsv[:,1] = np.minimum(self.patch_hsv[:,1]+patch_new,cv2.COLOR_BGR2HSV)[:]

patch_new = self.patch_hsv_temp[:,0)

self.patch_hsv_temp[:,cv2.COLOR_HSV2BGR)[:]

# 磨平

def smooth(self,rate=0.6,ksize=None,confirm=True):

if ksize == None:

ksize=self.get_ksize(80)

index = self.patch_mask > 0

if confirm:

self.confirm()

patch_new = cv2.GaussianBlur(cv2.bilateralFilter(self.patch_img,3,*ksize),0)

self.patch_img[index] = np.minimum(rate*patch_new[index]+(1-rate)*self.patch_img[index],255).astype('uint8')

self.img_hsv[:] = cv2.cvtColor(self.img,cv2.COLOR_BGR2HSV)[:]

self.update_temp()

else:

patch_new = cv2.GaussianBlur(cv2.bilateralFilter(self.patch_img_temp,0)

self.patch_img_temp[index] = np.minimum(rate*patch_new[index]+(1-rate)*self.patch_img_temp[index],255).astype('uint8')

self.patch_hsv_temp[:] = cv2.cvtColor(self.patch_img_temp,cv2.COLOR_BGR2HSV)[:]

# 锐化

def sharpen(self,confirm=True):

patch_mask = self.get_mask_relative((3,3))

kernel = np.zeros((9,9),np.float32)

kernel[4,4] = 2.0

boxFilter = np.ones((9,np.float32) / 81.0

kernel = kernel - boxFilter

index = patch_mask > 0

if confirm:

self.confirm()

sharp = cv2.filter2D(self.patch_img,-1,kernel)

self.patch_img[index] = np.minimum(((1-rate)*self.patch_img)[index]+sharp[index]*rate,255).astype('uint8')

self.update_temp()

else:

sharp = cv2.filter2D(self.patch_img_temp,kernel)

self.patch_img_temp[:] = np.minimum(self.patch_img_temp+self.patch_mask*sharp*rate,cv2.COLOR_BGR2HSV)[:]

# 额头

class ForeHead(Organ):

def __init__(self,mask_organs,ksize=None):

self.mask_organs = mask_organs

super(ForeHead,self).__init__(img,ksize)

# 获得局部相对坐标mask

def get_mask_relative(self,0) > 0) * 1.0

patch_organs = self.get_patch(self.mask_organs)

mask= cv2.GaussianBlur(mask,0)[:]

mask[patch_organs>0] = (1-patch_organs[patch_organs>0])

return mask

# 脸类

class Face(Organ):

def __init__(self,index):

self.index = index

# 五官：下巴、嘴、鼻子、左右眼、左右耳

self.organs_name = ['jaw','mouth','nose','left_eye','right_eye','left_brow','right_brow']

# 五官标记点

self.organs_point = [list(range(0,17)),list(range(48,61)),

list(range(27,35)),list(range(42,48)),

list(range(36,42)),list(range(22,27)),

list(range(17,22))]

self.organs = {name: Organ(img,landmarks[points],name) for name,points in zip(self.organs_name,self.organs_point)}

# 额头

mask_nose = self.organs['nose'].get_mask_abs()

mask_organs = (self.organs['mouth'].get_mask_abs()+mask_nose+self.organs['left_eye'].get_mask_abs()+self.organs['right_eye'].get_mask_abs()+self.organs['left_brow'].get_mask_abs()+self.organs['right_brow'].get_mask_abs())

forehead_landmark = self.get_forehead_landmark(img,mask_nose)

self.organs['forehead'] = ForeHead(img,forehead_landmark,'forehead')

mask_organs += self.organs['forehead'].get_mask_abs()

# 人脸的完整标记点

self.FACE_POINTS = np.concatenate([landmarks,forehead_landmark])

super(Face,self.FACE_POINTS,'face')

mask_face = self.get_mask_abs() - mask_organs

self.patch_mask = self.get_patch(mask_face)

# 计算额头坐标

def get_forehead_landmark(self,face_landmark,mask_nose):

radius = (np.linalg.norm(face_landmark[0]-face_landmark[16])/2).astype('int32')

center_abs = tuple(((face_landmark[0]+face_landmark[16])/2).astype('int32'))

angle = np.degrees(np.arctan((lambda l:l[1]/l[0])(face_landmark[16]-face_landmark[0]))).astype('int32')

mask = np.zeros(mask_organs.shape[:2],dtype=np.float64)

cv2.ellipse(mask,center_abs,(radius,radius),angle,180,360,1,-1)

# 剔除与五官重合部分

mask[mask_organs[:,0]>0]=0

# 根据鼻子的肤色判断真正的额头面积

index_bool = []

for ch in range(3):

mean,std = np.mean(img[:,ch][mask_nose[:,ch]>0]),np.std(img[:,ch]>0])

up,down = mean+0.5*std,mean-0.5*std

index_bool.append((img[:,ch]up))

index_zero = ((mask>0)&index_bool[0]&index_bool[1]&index_bool[2])

mask[index_zero] = 0

index_abs = np.array(np.where(mask>0)[::-1]).transpose()

landmark = cv2.convexHull(index_abs).squeeze()

return landmark

# 化妆器

class Makeup():

def __init__(self,predictor_path='./predictor/shape_predictor_68_face_landmarks.dat'):

self.photo_path = []

self.predictor_path = predictor_path

self.faces = {}

# 人脸检测与特征提取

self.detector = dlib.get_frontal_face_detector()

self.predictor = dlib.shape_predictor(self.predictor_path)

# 人脸定位和特征提取

# img为numpy数组

# 返回值为人脸特征(x,y)坐标的矩阵

def get_faces(self,n=1):

rects = self.detector(img,1)

if len(rects) < 1:

print('[Warning]:No face detected...')

return None

return {name: [Face(img,np.array([[p.x,p.y] for p in self.predictor(img,rect).parts()]),i) for i,rect in enumerate(rects)]}

# 读取图片

def read_img(self,fname,scale=1):

img = cv2.imdecode(np.fromfile(fname,dtype=np.uint8),-1)

if not type(img):

print('[ERROR]:Fail to Read %s' % fname)

return None

return img

def read_and_mark(self,fname):

img = self.read_img(fname)

img_hsv = cv2.cvtColor(img,cv2.COLOR_BGR2HSV)

temp_img,temp_hsv = img.copy(),img_hsv.copy()

return img,self.get_faces(img,fname))|(img[:,>

效果如下：

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​​嘿嘿——小姐姐美颜之后是不是白了很多吖！

总结

本次文章就到这里啦！如需完整地打包好的项目源码基地见：【私信小编06】即可免费领取！

记得关注、评论、点赞三连哦~

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