我有一个图像,其中包含一些米手写的值,我想找到字母m的位置,所以我可以裁剪它,只留下数字.
这是一个例子：
原始图像：输入图像如下所示,实际上这是我能得到的最好的手写输入,通常情况会更糟.
火车图像：我有一个m字母的列表,从我有的不同手写图像切割.
结果图：我想得到的结果
我已经尝试过使用opencv模板匹配功能,但它不起作用,也发现这个github,但它也使用模板匹配.@H_502_18@我想知道是否还有其他方法可以解决这个问题.
最佳答案
似乎这封信总是在数字的末尾.如果是这样,您可以采用更简单的方法：
原文链接：https://www.f2er.com/python/438843.html>找到所有轮廓;
>创建边界框列表(即每个轮廓一个框);
>确定哪一个是最右边的边界框;
>使用所有其他框的(x,y,宽度,高度)信息来创建ROI并仅裁剪数字;
Python 2.7和OpenCV 2.4的源代码：
import cv2
### load input image and convert it to grayscale
img = cv2.imread("input.png")
print("img shape=",img.shape)
gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
#### extract all contours
_,contours,_ = cv2.findContours(gray.copy(),cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)
# debug: draw all contours
#cv2.drawContours(img,-1,(0,255),2)
#cv2.imwrite("all_contours.jpg",img)
#### create one bounding Box for every contour found
bb_list = []
for c in contours:
bb = cv2.boundingRect(c)
# save all Boxes except the one that has the exact dimensions of the image (x,width,height)
if (bb[0] == 0 and bb[1] == 0 and bb[2] == img.shape[1] and bb[3] == img.shape[0]):
continue
bb_list.append(bb)
# debug: draw Boxes
#img_Boxes = img.copy()
#for bb in bb_list:
# x,w,h = bb
# cv2.rectangle(img_Boxes,(x,y),(x+w,y+h),2)
#cv2.imwrite("Boxes.jpg",img_Boxes)
#### sort bounding Boxes by the X value: first item is the left-most Box
bb_list.sort(key=lambda x:x[0])
# debug: draw the last Box of the list (letter M)
#print("letter M @ ",bb_list[-1])
#x,h = bb_list[-1]
#cv2.rectangle(img,2)
#cv2.imwrite("last_contour.jpg",img)
### remove the last item from the list,i.e. remove Box for letter M
bb_list = bb_list[:-1]
### and now the fun part: create one large bounding Box to rule them all
x_start,_,_ = bb_list[0]
x_end,w_end,_ = bb_list[-1]
x = x_start
w = (x_end + w_end) - x_start
bb_list.sort(key=lambda y:y[1]) # sort by Y value: the first item has the smallest Y value
_,_ = bb_list[0]
bb_list.sort(key=lambda y:y[3]) # sort by Height value: the last item has the largest Height value
_,h = bb_list[-1]
print("x=",x,"y=","w=","h=",h)
# debug: draw the final region of interest
roi_img = img.copy()
cv2.rectangle(roi_img,2)
cv2.imwrite("roi.jpg",roi_img)
# crop to the roi
crop_img = img[y:y+h,x:x+w]
cv2.imwrite("crop.jpg",crop_img)