如何找到图像中物体的中心和角度？

Question

我正在使用 python 和 OpenCV。我正在寻找电池的中心和角度：

Image of batteries with random angles:

我的代码是这样的：

import cv2
import numpy as np


img = cv2.imread('image/baterias2.png')
gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
img2 = cv2.imread('image/baterias4.png',0)


minLineLength = 300
maxLineGap = 5

edges = cv2.Canny(img2,50,200)
cv2.imshow('Canny',edges)
lines = cv2.HoughLinesP(edges,1,np.pi/180,80,minLineLength,maxLineGap)
print lines
salida = np.zeros((img.shape[0],img.shape[1]))
for x in range(0, len(lines)):
    for x1,y1,x2,y2 in lines[x]:
        cv2.line(salida,(x1,y1),(x2,y2),(125,125,125),0)#  rgb


cv2.imshow('final',salida)
cv2.imwrite('result/hough.jpg',img)
cv2.waitKey(0)

有什么想法可以解决吗？

Answer 1

几乎与one of my other answers 相同。 PCA 似乎工作正常。

import cv2
import numpy as np

img = cv2.imread("test_images/battery001.png")  #load an image of a single battery
img_gs = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)  #convert to grayscale

#inverted binary threshold: 1 for the battery, 0 for the background
_, thresh = cv2.threshold(img_gs, 250, 1, cv2.THRESH_BINARY_INV)

#From a matrix of pixels to a matrix of coordinates of non-black points.
#(note: mind the col/row order, pixels are accessed as [row, col]
#but when we draw, it's (x, y), so have to swap here or there)
mat = np.argwhere(thresh != 0)

#let's swap here... (e. g. [[row, col], ...] to [[col, row], ...])
mat[:, [0, 1]] = mat[:, [1, 0]]
#or we could've swapped at the end, when drawing
#(e. g. center[0], center[1] = center[1], center[0], same for endpoint1 and endpoint2),
#probably better performance-wise


mat = np.array(mat).astype(np.float32) #have to convert type for PCA

#mean (e. g. the geometrical center) 
#and eigenvectors (e. g. directions of principal components)
m, e = cv2.PCACompute(mat, mean = np.array([]))

#now to draw: let's scale our primary axis by 100, 
#and the secondary by 50

center = tuple(m[0])
endpoint1 = tuple(m[0] + e[0]*100)
endpoint2 = tuple(m[0] + e[1]*50)

red_color = (0, 0, 255)
cv2.circle(img, center, 5, red_color)
cv2.line(img, center, endpoint1, red_color)
cv2.line(img, center, endpoint2, red_color)
cv2.imwrite("out.png", img)

Answer 2

• 要找出对象的中心，您可以使用Moments。 用findContours对图像进行阈值化，得到物体的轮廓。 用cv.Moments(arr, binary=0) → moments 计算矩。 作为arr，您可以通过轮廓。然后中心的坐标计算为x = m10/m00和y = m01/m00。

• 要获得方向，您可以在对象周围绘制一个最小矩形并计算矩形较长边与垂直线之间的角度。

Answer 3

您可以参考代码。

import cv2
import imutils
import numpy as np

PIC_PATH = r"E:\temp\Battery.jpg"    

image = cv2.imread(PIC_PATH)

gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
blurred = cv2.GaussianBlur(gray, (5, 5), 0)    

edged = cv2.Canny(gray, 100, 220)

kernel = np.ones((5,5),np.uint8)
closed = cv2.morphologyEx(edged, cv2.MORPH_CLOSE, kernel)

cnts = cv2.findContours(closed.copy(), cv2.RETR_EXTERNAL,
    cv2.CHAIN_APPROX_SIMPLE)
cnts = cnts[0] if imutils.is_cv2() else cnts[1]

cv2.drawContours(image, cnts, -1, (0, 255, 0), 4)

cv2.imshow("Output", image)
cv2.waitKey(0)

结果图片是，