如何在opencv和python中使眼睛和鼻子變大或變小

我使用以下代碼在 OpenCV 和 Python 中選擇鼻子我搜索了很多以找到一種方法來更改鼻子的大小并另存為其他影像，但我沒有找到任何人可以幫助我做到這一點。

import cv2
import numpy as np
import dlib
img = cv2.imread('1.jpg')
img = cv2.resize(img,(0,0),None,0.5,0.5)
imgOriginal = img.copy()

detector = dlib.get_frontal_face_detector()
predictor = dlib.shape_predictor("shape_predictor_68_face_landmarks.dat")

def createBox(img,points,scale=5):
  bbox = cv2.boundingRect(points)
  x,y,w,h = bbox
  imgCrop = img[y:y h,x:x w]
  imgCrop = cv2.resize(imgCrop,(0,0),None,scale,scale)
  return imgCrop


imgGray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
faces = detector(imgGray)
for face in faces:
  x1,y1 = face.left(),face.top()
  x2,y2 = face.right(),face.bottom()
  imgOriginal = cv2.rectangle(img,(x1,y1),(x2,y2),(0,255,0),1)
  landmarks = predictor(imgGray,face)
  myPoints=[]
  for n in range(68):
    x = landmarks.part(n).x
    y = landmarks.part(n).y
    myPoints.append([x,y])
    #cv2.circle(imgOriginal,(x,y),5,(50,50,255),cv2.FILLED)
    #cv2.putText(imgOriginal,str(n),(x,y-10),cv2.FONT_HERSHEY_COMPLEX_SMALL,0.8,(0,0,255),1)
  myPoints = np.array(myPoints)
  #nose points to select
  #nose_points = myPoints[27:35]

print(myPoints)
cv2_imshow(imgOriginal)
cv2.waitKey(0)

提前致謝

uj5u.com熱心網友回復：

我認為您需要“Bulge”效果，例如內爆和爆炸。OpenCV 中沒有這些過濾器的實作，但是，您可以找到其他工具，例如具有

import numpy as np
import cv2
import math
import skimage.exposure

img = cv2.imread("portrait_of_mussorgsky2.jpg")

# set location and radius
cx = 130
cy = 109
radius = 30

# set distortion gain
gain = 1.5

# crop image 
crop = img[cy-radius:cy radius, cx-radius:cx radius]

# get dimensions
ht, wd = crop.shape[:2]
xcent = wd / 2
ycent = ht / 2
rad = min(xcent,ycent)

# set up the x and y maps as float32
map_x = np.zeros((ht, wd), np.float32)
map_y = np.zeros((ht, wd), np.float32)
mask = np.zeros((ht, wd), np.uint8)

# create map with the spherize distortion formula --- arcsin(r)
# xcomp = arcsin(r)*x/r; ycomp = arsin(r)*y/r
for y in range(ht):
    Y = (y - ycent)/ycent
    for x in range(wd):
        X = (x - xcent)/xcent
        R = math.hypot(X,Y)
        if R == 0:
            map_x[y, x] = x
            map_y[y, x] = y
            mask[y,x] = 255
        elif R >= .90:    # avoid extreme blurring near R = 1
            map_x[y, x] = x
            map_y[y, x] = y
            mask[y,x] = 0
        elif gain >= 0:
            map_x[y, x] = xcent*X*math.pow((2/math.pi)*(math.asin(R)/R), gain)   xcent
            map_y[y, x] = ycent*Y*math.pow((2/math.pi)*(math.asin(R)/R), gain)   ycent
            mask[y,x] = 255
        elif gain < 0:
            gain2 = -gain
            map_x[y, x] = xcent*X*math.pow((math.sin(math.pi*R/2)/R), gain2)   xcent
            map_y[y, x] = ycent*Y*math.pow((math.sin(math.pi*R/2)/R), gain2)   ycent
            mask[y,x] = 255

# remap using map_x and map_y
bump = cv2.remap(crop, map_x, map_y, cv2.INTER_LINEAR, borderMode = cv2.BORDER_CONSTANT, borderValue=(0,0,0))

# antialias edge of mask
# (pad so blur does not extend to edges of image, then crop later)
blur = 7
mask = cv2.copyMakeBorder(mask, blur,blur,blur,blur, borderType=cv2.BORDER_CONSTANT, value=(0))
mask = cv2.GaussianBlur(mask, (0,0), sigmaX=blur, sigmaY=blur, borderType = cv2.BORDER_DEFAULT)
h, w = mask.shape
mask = mask[blur:h-blur, blur:w-blur]
mask = cv2.cvtColor(mask, cv2.COLOR_GRAY2BGR)
mask = skimage.exposure.rescale_intensity(mask, in_range=(127.5,255), out_range=(0,1))

# merge bump with crop using grayscale (not binary) mask
bumped = (bump * mask   crop * (1-mask)).clip(0,255).astype(np.uint8)

# insert bumped image into original
result = img.copy()
result[cy-radius:cy radius, cx-radius:cx radius] = bumped

# save results
cv2.imwrite("portrait_of_mussorgsky2_bump.jpg", result)

# display images
cv2.imshow('img', img)
cv2.imshow('crop', crop)
cv2.imshow('bump', bump)
cv2.imshow('mask', mask)
cv2.imshow('bumped', bumped)
cv2.imshow('result', result)
cv2.waitKey(0)
cv2.destroyAllWindows()

結果影像：

標籤：Python opencv 图像处理 数据库

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