边缘检测图像中的物体识别？

Question

请使用轮廓帮助我识别边缘检测图像。这是我使用此代码的部分，我可以分离一些图像，但在大型详细图像中很难。我该如何修改

import numpy as np
import cv2

# load image
img = cv2.imread('res/test6.jpg', 1)

# convert the image to grayscale, blur it, and detect edges
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
gray = cv2.GaussianBlur(gray, (5, 5), 0)
edged = cv2.Canny(gray, 35, 125)
height, width = edged.shape

# find contours of object
ret, thresh = cv2.threshold(edged, 127, 255, 0)
contours = cv2.findContours(thresh, 1, 2)
cnts = contours[1]
for cnt in cnts:
    # find and draw a rectangle around object
    x, y, w, h = cv2.boundingRect(cnt)
    cv2.rectangle(img, (x, y), (x + w, y + h), (0, 255, 0), 2)

    # line parameter
    x1 = x + w / 2
    y1 = y + h
    x2 = x + w / 2
    y2 = height

    # mark pixel depth with arrow
    cv2.arrowedLine(img, (x2, y2), (x1, y1), (255, 0, 0), 4)
    distance = (y2 - y1) * 0.03 + 4

    cv2.putText(img, str(distance) + "m", (x1 + 5, y1 + 50), cv2.FONT_HERSHEY_SIMPLEX, 0.5, 255)

    print height, width

cv2.imshow('image', img)
cv2.waitKey(0)
cv2.destroyAllWindows()
import numpy as np
import cv2

# load image
img = cv2.imread('res/test6.jpg', 1)

# convert the image to grayscale, blur it, and detect edges
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
gray = cv2.GaussianBlur(gray, (5, 5), 0)
edged = cv2.Canny(gray, 35, 125)
height, width = edged.shape

# find contours of object
ret, thresh = cv2.threshold(edged, 127, 255, 0)
contours = cv2.findContours(thresh, 1, 2)
cnts = contours[1]
for cnt in cnts:
    # find and draw a rectangle around object
    x, y, w, h = cv2.boundingRect(cnt)
    cv2.rectangle(img, (x, y), (x + w, y + h), (0, 255, 0), 2)

    # line parameter
    x1 = x + w / 2
    y1 = y + h
    x2 = x + w / 2
    y2 = height

    # mark pixel depth with arrow
    cv2.arrowedLine(img, (x2, y2), (x1, y1), (255, 0, 0), 4)
    distance = (y2 - y1) * 0.03 + 4

    cv2.putText(img, str(distance) + "m", (x1 + 5, y1 + 50), cv2.FONT_HERSHEY_SIMPLEX, 0.5, 255)

    print height, width

cv2.imshow('image', img)
cv2.waitKey(0)
cv2.destroyAllWindows()

我想要的是限制识别对象。

Answer 1

从给定的代码中，我猜你已经使用轮廓识别了对象。然后你用矩形绑定了那些轮廓。

现在更进一步。找到绑定刚刚获得的轮廓的矩形的质心。测量从质心到图像底部的距离。

for c in cnts:
   ------# compute the center of the contour
   M = cv2.moments(c)
   cX = int(M["m10"] / M["m00"])
   cY = int(M["m01"] / M["m00"])

   ------# draw the contour and center of the shape on the image
   cv2.drawContours(image, [c], -1, (0, 255, 0), 2)
   cv2.circle(image, (cX, cY), 7, (255, 255, 255), -1)

   ------# show the image
   cv2.imshow("Image", image)

我遇到了THIS POST，这帮助了我解答。

为了更好地了解图像时刻，我建议维基百科THIS ARTICLE。