如何查找图像中物体的中心和角度?
问题描述:
我正在使用Python和OpenCV。我试图找到电池的中心和角度:如何查找图像中物体的中心和角度?
Image of batteries with random angles:
比我的代码是这样的:
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)
任何想法去解决它?
答
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)
结果画面,
+0
OP想要找到每个单元格的中心和角度 – ZdaR
答
几乎相同one of my other answers。 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
ret, thresh = cv2.threshold(img_gs, 250, 1, cv2.THRESH_BINARY) #binary threshold
thresh = 1 - thresh #invert: 1 for the battery, 0 for the background
h, w = thresh.shape
#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 = [[col, row] for col in range(w) for row in range(h) if thresh[row, col] != 0]
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)
答
要找出一个物体的中心,你可以使用Moments。 对图像进行阈值并使用findContours获取对象的轮廓。 用
cv.Moments(arr, binary=0) → moments
计算矩。 由于arr
你可以通过轮廓。然后中心的坐标计算为x = m10/m00
和y = m01/m00
。要获取方向,可以在对象周围画一个最小的矩形并计算矩形的长边和垂直线之间的角度。
你试过了什么? – saul
你好。我正在尝试这个步骤:1.门槛,2. Canny,3.线条,但显示我不完整的线条。 –
请分享您使用过的代码以及当前的输出结果吗? – ZdaR