opencv摳圖並面部檢測後新增聖誕帽
從網上獲取trump的頭像, 再使用eigenfacerecognizer_create單獨識別出trump
#構建mask
hsv=cv2.cvtcolor(hat,cv2.color_rgb2hsv)
black_lower=np.array([0,0,0])
black_upper=np.array([180,180,180])
mask=cv2.inrange(hsv,black_lower,black_upper)
#cv2.imshow('mask',mask)
#腐蝕膨脹
erode=cv2.erode(mask,none,iterations=1)
#cv2.imshow('erode',erode)
dilate=cv2.dilate(erode,none,iterations=1)
#cv2.imshow('dilate',dilate)
def detect(filename):
face_cascade=cv2.cascadeclassifier('haarcascade_frontalface_default.xml')
img=cv2.imread(filename)
gray=cv2.cvtcolor(img,cv2.color_bgr2gray)
faces=face_cascade.detectmultiscale(gray,scalefactor=1.055,minneighbors=5,minsize=(30,30))
for (x,y,w,h) in faces:
#img=cv2.rectangle(img,(x,y),(x+w,y+h),(255,0,0),2)#面部識別方框
sp=hat.shape
hatsizeh=int(sp[0]/sp[1]*w)
if hatsizeh>y:
hatsizeh=y
hatresize=cv2.resize(hat,(w,hatsizeh),interpolation=cv2.inter_nearest)
dilateresize=cv2.resize(dilate,(w,hatsizeh),interpolation=cv2.inter_nearest)
top=y-hatsizeh
if top<=0:
top=0
rows,cols,channels=hatresize.shape
roi=img[top:top+rows,x:x+cols]
for i in range(rows):
for j in range(cols):
if dilateresize[i,j]==0:#0代表黑色的點
img[top+i,x+j]=hatresize[i,j]#此處替換顏色，為bgr通道
計組令人窒息, 丟下**就跑, 有空再更
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