我之前问了一个可能太复杂的问题。所以我在这里有一个新的更简单。
我有两张图片:
我想要做的是将第二张图像置于第一张图像的中心,如下图所示。
到目前为止,我所取得的成就是这些影像的中心。
该值是两个点的列表,X-Y。
如何匹配这些点以获得上述所需的结果?
import cv2
import numpy as np
import os
img1 = cv2.imread(os.path.expanduser('~\\Desktop\\c1.png'))
# ---Read image and obtain threshold---
img0 = cv2.cvtColor(img1, cv2.COLOR_BGR2GRAY)
ret, thresh = cv2.threshold(img0, 120, 255, 1)
# ---Obtain contours---
image, contours, hierarchy = cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
cnts = contours
center = []
for c in cnts:
M = cv2.moments(c)
cX = int(M["m10"] / M["m00"])
cY = int(M["m01"] / M["m00"])
print(cX, cY)
center.append(cX)
center.append(cY)
print(center)
由于
答案 0 :(得分:3)
这是我的步骤:
- 按轮廓查找中心
- 计算中心之间的偏移量
- 切片操作到
醇>paste
对象图像
对于这两张图片:
这是我的结果(对于img2为0.3x):
#!/usr/bin/python3
# 2018.01.16 21:07:48 CST
# 2018.01.16 21:23:47 CST
import cv2
import numpy as np
import os
def findCenter(img):
print(img.shape, img.dtype)
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
th, threshed = cv2.threshold(gray, 127, 255, cv2.THRESH_BINARY_INV|cv2.THRESH_OTSU)
#cv2.imshow("threshed", threshed);cv2.waitKey();cv2.destroyAllWindows()
#_, cnts, hierarchy = cv2.findContours(threshed, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
cnts = cv2.findContours(threshed, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)[-2]
M = cv2.moments(cnts[0])
cX = int(M["m10"] / M["m00"])
cY = int(M["m01"] / M["m00"])
return (cX,cY)
img1 = cv2.imread("img1.jpg")
img2 = cv2.resize(cv2.imread("img2.jpg"), None, fx=0.3, fy=0.3)
## (1) Find centers
pt1 = findCenter(img1)
pt2 = findCenter(img2)
## (2) Calc offset
dx = pt1[0] - pt2[0]
dy = pt1[1] - pt2[1]
## (3) do slice-op `paste`
h,w = img2.shape[:2]
dst = img1.copy()
dst[dy:dy+h, dx:dx+w] = img2
cv2.imwrite("res.png", dst)