我正在尝试使用OpenCV Python在我自己的直播视频流上叠加衬衫图像。三天以来我一直坚持这个特殊的错误：
错误：（-215）（mtype == CV_8U || mtype == CV_8S）＆amp;＆amp;函数cv :: binary_op
中的_mask.sameSize（* psrc1）此错误发生在此行：
roi_bg = cv2.bitwise_and（roi，roi，mask = mask_inv）
我的代码：
import cv2 # Library for image processing
import numpy as np
imgshirt = cv2.imread('C:/Users/sayyed javed ahmed/Desktop/Humaira/Images For Programs/aureknayashirt.png',1) #original img in bgr
musgray = cv2.cvtColor(imgshirt,cv2.COLOR_BGR2GRAY) #grayscale conversion
ret, orig_mask = cv2.threshold(musgray,150 , 255, cv2.THRESH_BINARY)
orig_mask_inv = cv2.bitwise_not(orig_mask)
origshirtHeight, origshirtWidth = imgshirt.shape[:2]
face_cascade=cv2.CascadeClassifier('C:\Users\sayyed javed ahmed\Desktop\Humaira\haarcascade_frontalface_default.xml')
cap=cv2.VideoCapture(0)
while True:
ret,img=cap.read()
gray=cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
faces=face_cascade.detectMultiScale(gray,1.3,5)
for (x,y,w,h) in faces:
cv2.rectangle(img,(x,y),(x+w,y+h),(255,0,0),2)
shirtWidth = 3 * w #approx wrt face width
shirtHeight = shirtWidth * origshirtHeight / origshirtWidth #preserving aspect ratio of original image..
# Center the shirt..just random calculations..
x1 = x-w
x2 =x1+3*w
y1 = y+h
y2 = y1+h*2
# Check for clipping(whetehr x1 is coming out to be negative or not..)
if x1 < 0:
x1 = 0
if y1 < 0:
y1 = 0
if x2 > 4*w:
x2 =4*w
if y2 > 2* h:
y2 = x2* origshirtHeight / origshirtWidth
print x1 #debugging
print x2
print y1
print y2
print w
print h
# Re-calculate the width and height of the shirt image(to resize the image when it wud be pasted)
shirtWidth = x2 - x1
shirtHeight = y2 - y1
# Re-size the original image and the masks to the shirt sizes
shirt = cv2.resize(imgshirt, (shirtWidth,shirtHeight), interpolation = cv2.INTER_AREA) #resize all,the masks you made,the originla image,everything
mask = cv2.resize(orig_mask, (shirtWidth,shirtHeight), interpolation = cv2.INTER_AREA)
mask_inv = cv2.resize(orig_mask_inv, (shirtWidth,shirtHeight), interpolation = cv2.INTER_AREA)
# take ROI for shirt from background equal to size of shirt image
roi = img[y1:y2, x1:x2]
print shirt.size #debugginh
print mask.size
print mask_inv.size
print roi.size
print shirt.shape
print roi.shape
print mask.shape
print mask_inv.shape
# roi_bg contains the original image only where the shirt is not
# in the region that is the size of the shirt.
roi_bg = cv2.bitwise_and(roi,roi,mask = mask_inv)
# roi_fg contains the image of the shirt only where the shirt is
roi_fg = cv2.bitwise_and(shirt,shirt,mask = mask)
print roi_bg.shape #debugging
print roi_fg.shape
# join the roi_bg and roi_fg
dst = cv2.add(roi_bg,roi_fg)
print dst.shape
# place the joined image, saved to dst back over the original image
roi = dst
break
cv2.imshow('img',img)
if cv2.waitKey(1) == ord('q'):
break;
cap.release() # Destroys the cap object
cv2.destroyAllWindows() # Destroys all the windows created by imshow
我读过这个帖子： http://www.stackoverflow.com/questions/30117740/opencv-error-assertion-failed-mask-size-src1-size-in-binary-op 但还没有掌握太多。我知道roi和衬衫的尺寸应该相同，我打印这些值来检查它们是否相同，但它们不是。根据我的说法：
roi = img [y1：y2，x1：x2]
和
shirt = cv2.resize（imgshirt，（shirtWidth，shirtHeight），interpolation = cv2.INTER_AREA）
应该将它们的大小都设为x2-x1和y2-y1，但这并没有发生。从三天开始，我一直在这条线上摸不着头脑，任何帮助都表示赞赏！
答案 0 :(得分：2)
您是否确保叠加的图像不会超过前景尺寸，因为这通常会导致遮罩尺寸不同
答案 1 :(得分：2)
错误很可能来自你摆弄x和y变量和衬衫尺码的地方，而不确定它们是否适合网络摄像头饲料的框架。
我将您的代码重新编写为工作代码：
import cv2
import numpy as np
imgshirt = cv2.imread('shirt.png',1)
musgray = cv2.cvtColor(imgshirt,cv2.COLOR_BGR2GRAY) #grayscale conversion
ret, orig_mask = cv2.threshold(musgray,150 , 255, cv2.THRESH_BINARY)
orig_mask_inv = cv2.bitwise_not(orig_mask)
origshirtHeight, origshirtWidth = imgshirt.shape[:2]
face_cascade=cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
cap=cv2.VideoCapture(0)
ret,img=cap.read()
img_h, img_w = img.shape[:2]
while True:
ret,img=cap.read()
gray=cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
faces=face_cascade.detectMultiScale(gray,1.3,5)
for (x,y,w,h) in faces:
cv2.rectangle(img,(x,y),(x+w,y+h),(255,0,0),2)
face_w = w
face_h = h
face_x1 = x
face_x2 = face_x1 + face_h
face_y1 = y
face_y2 = face_y1 + face_h
# set the shirt size in relation to tracked face
shirtWidth = 3 * face_w
shirtHeight = int(shirtWidth * origshirtHeight / origshirtWidth)
shirt_x1 = face_x2 - int(face_w/2) - int(shirtWidth/2) #setting shirt centered wrt recognized face
shirt_x2 = shirt_x1 + shirtWidth
shirt_y1 = face_y2 + 5 # some padding between face and upper shirt. Depends on the shirt img
shirt_y2 = shirt_y1 + shirtHeight
# Check for clipping
if shirt_x1 < 0:
shirt_x1 = 0
if shirt_y1 < 0:
shirt_y1 = 0
if shirt_x2 > img_w:
shirt_x2 = img_w
if shirt_y2 > img_h:
shirt_y2 = img_h
shirtWidth = shirt_x2 - shirt_x1
shirtHeight = shirt_y2 - shirt_y1
if shirtWidth < 0 or shirtHeight < 0:
continue
# Re-size the original image and the masks to the shirt sizes
shirt = cv2.resize(imgshirt, (shirtWidth,shirtHeight), interpolation = cv2.INTER_AREA) #resize all,the masks you made,the originla image,everything
mask = cv2.resize(orig_mask, (shirtWidth,shirtHeight), interpolation = cv2.INTER_AREA)
mask_inv = cv2.resize(orig_mask_inv, (shirtWidth,shirtHeight), interpolation = cv2.INTER_AREA)
# take ROI for shirt from background equal to size of shirt image
roi = img[shirt_y1:shirt_y2, shirt_x1:shirt_x2]
# roi_bg contains the original image only where the shirt is not
# in the region that is the size of the shirt.
roi_bg = cv2.bitwise_and(roi,roi,mask = mask)
roi_fg = cv2.bitwise_and(shirt,shirt,mask = mask_inv)
dst = cv2.add(roi_bg,roi_fg)
img[shirt_y1:shirt_y2, shirt_x1:shirt_x2] = dst
break
cv2.imshow('img',img)
if cv2.waitKey(1) == ord('q'):
break;
cap.release() # Destroys the cap object
cv2.destroyAllWindows() # Destroys all the windows created by imshow
我重命名变量以使它们更容易掌握。我将衬衫图像和haarcascade XML路径设置为工作目录以进行本地测试。我在创建roi bg和fg时也切换了面具，不完全确定为什么这是必要的，但这给出了正确的结果。最后添加了img[shirt_y1:shirt_y2, shirt_x1:shirt_x2] = dst以将衬衫粘贴到视频帧中。
另外需要注意的是，在使用numpy图像时，请始终将任何分割结果转换为int s。
答案 2 :(得分：-1)
如果掩码的数据类型不正确，也会发生类似的错误。有关更多详细信息，请参见this
