OpenCV Python错误:错误:(-215)(mtype == CV_8U || mtype == CV_8S)&&函数cv :: binary_op中的_mask.sameSize(* psrc1) [英] OpenCV Python Error: error: (-215) (mtype == CV_8U || mtype == CV_8S) && _mask.sameSize(*psrc1) in function cv::binary_op
问题描述
我正在尝试使用OpenCV Python在我自己的实时视频流上覆盖衬衫的图像.自三天以来，我一直被这个错误困住:
I'm trying to overlay an image of shirt on live video stream of myself using OpenCV Python. I'm stuck at this particular error since three days:
错误:(-215)(mtype == CV_8U || mtype == CV_8S)&&函数cv :: binary_op中的_mask.sameSize(* psrc1)
error: (-215) (mtype == CV_8U || mtype == CV_8S) && _mask.sameSize(*psrc1) in function cv::binary_op
此错误发生在此行:
roi_bg = cv2.bitwise_and(roi，roi，mask = mask_inv)
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
我已阅读此主题: 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.我知道投资回报率和衬衫的尺寸应该相同，我打印出值来检查它们是否相同，但不相同.据我说:
I've read this thread: http://www.stackoverflow.com/questions/30117740/opencv-error-assertion-failed-mask-size-src1-size-in-binary-op but haven't grasped much. I know that the size of roi and shirt should be same,I printed the values to check if they're the same but they aren't. According to me the statements:
roi = img [y1:y2，x1:x2]
roi = img[y1:y2, x1:x2]
和
shirt = cv2.resize(imgshirt，(shirtWidth，shirtHeight)，插值= cv2.INTER_AREA)
shirt = cv2.resize(imgshirt, (shirtWidth,shirtHeight), interpolation = cv2.INTER_AREA)
应将它们的大小都设置为x2-x1和y2-y1，但这没有发生.自三天以来，我一直在这条线上挠头，不胜感激！
should make both their sizes as x2-x1 and y2-y1 but that's not happening. Been scratching my head over this one line since three days,any help is appreciated!
推荐答案
该错误很可能是由于您在不确定x和y变量以及衬衫大小的地方弄错了，而又不确定它们是否适合网络摄像头供稿的框架.
The error most likely came from where you fiddled with x and y variables and shirt size without making sure they fit inside the frame of the webcam feed.
我将您的代码重新编写为有效的代码:
I reworked your code into a working one:
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
我重命名了变量，以使它们更易于掌握.我将衬衫图像和haarcascade XML路径设置为用于本地测试的工作目录.在创建roi bg和fg时，我也切换了蒙版，虽然不确定是否需要这样做，但是给出了正确的结果.最后添加了img[shirt_y1:shirt_y2, shirt_x1:shirt_x2] = dst实际上将衬衫粘贴到视频帧中.
I renamed variables to make them easier to grasp. I set the shirt image and haarcascade XML paths to working directory for local testing. I also switched masks when creating roi bg and fg, not exactly sure why that was necessary, but that gave the correct outcome. Finally added img[shirt_y1:shirt_y2, shirt_x1:shirt_x2] = dst to actually paste the shirt into the video frame.
要注意的另一件事是，使用numpy图像时，请始终将除法结果转换为int s.
Another thing to note is when working with numpy images, always convert any division results into ints.
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