python - 查找轮廓和边界以获取图像内部的点 OpenCV Python

标签 python image-processing

我有一个代码可以在图像中绘制对象的轮廓,然后在它们周围绘制一个矩形。我需要找到形状中最宽的直径(两点)女巫是水平直线现在我需要找到对象边界内的点(像素坐标)。

这是我的代码:

Picture for Reference

class App:
    def __init__(self, window, window_title, image_path="ex.jpg"):
        self.window = window
        self.window.title(window_title)

        # Load an image using OpenCV
        self.cv_img = cv2.cvtColor(cv2.imread(image_path), cv2.COLOR_BGR2RGB)

        # Get the image dimensions (OpenCV stores image data as NumPy ndarray)
        self.height, self.width, no_channels = self.cv_img.shape

        # Create a canvas that can fit the above image
        self.canvas = tkinter.Canvas(window, width = self.width, height = self.height)
        self.canvas.pack()

        # Use PIL (Pillow) to convert the NumPy ndarray to a PhotoImage
        self.photo = PIL.ImageTk.PhotoImage(image = PIL.Image.fromarray(self.cv_img))

        # Add a PhotoImage to the Canvas
        self.canvas.create_image(0, 0, image=self.photo, anchor=tkinter.NW)

        # Button that lets the user blur the image
        self.btn_blur=tkinter.Button(window, text="Blur", width=25, command=self.blur_image)
        self.btn_blur.pack(anchor=tkinter.CENTER, expand=True)

        # Button that lets the user edeged the image
        self.btn_blur=tkinter.Button(window, text="edged", width=25, command=self.edged_image)
        self.btn_blur.pack(anchor=tkinter.CENTER, expand=True)

        # Button that lets the user edeged the image
        self.btn_blur=tkinter.Button(window, text="draw box", width=25, command=self.draw_box)
        self.btn_blur.pack(anchor=tkinter.CENTER, expand=True)

        self.window.mainloop()

    # Callback for the "Blur" button
    def blur_image(self):
        self.cv_img = cv2.blur(self.cv_img, (3, 3))
        self.photo = PIL.ImageTk.PhotoImage(image = PIL.Image.fromarray(self.cv_img))
        self.canvas.create_image(0, 0, image=self.photo, anchor=tkinter.NW)

    # Callback for the "edged" button
    def edged_image(self):
        #edeged image
        self.cv_img=cv2.Canny(self.cv_img,50,180)
        self.cv_img = cv2.dilate(self.cv_img, None, iterations=1)
        self.cv_img = cv2.erode(self.cv_img, None, iterations=1)
        self.photo = PIL.ImageTk.PhotoImage(image = PIL.Image.fromarray(self.cv_img))
        self.canvas.create_image(0, 0, image=self.photo, anchor=tkinter.NW)

    # Callback for the "draw contours" button
    def draw_box(self):        
        #draw contour
        cnts = cv2.findContours(self.cv_img.copy(), cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE)
        cnts = cnts[0] if imutils.is_cv2() else cnts[1]
        #draw box
        for c in cnts:
            self.cv_img = cv2.drawContours(self.cv_img, [c], 0, (0,255,0), 3)
            x,y,w,h = cv2.boundingRect(c)
            self.cv_img = cv2.rectangle(self.cv_img,(x,y),(x+w,y+h),(0,255,0),2)

#Create a window and pass it to the Application object
App(tkinter.Tk(), "morteza app")

最佳答案

您可以尝试找到极值点(在您的情况下为左、右和上)。然后,您可以使用计算两点之间距离的公式 d=sqrt((x2-x1)^2 + (y2-y1)^2) 来计算从极左到极右的距离。如果您愿意,您甚至可以使用相同的原理找到线的中心并计算线的中心与最高点之间的距离。这是一个示例代码:

import numpy as np
import cv2
import imutils

img = cv2.imread('bulb.png')


gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
ret, thresh = cv2.threshold(gray, 240, 255, cv2.THRESH_BINARY)
cv2.bitwise_not(thresh, thresh)

cnts = cv2.findContours(thresh, cv2.RETR_EXTERNAL,
                cv2.CHAIN_APPROX_SIMPLE)
cnts = cnts[0]
c = max(cnts, key=cv2.contourArea)

left = tuple(c[c[:, :, 0].argmin()][0])
right = tuple(c[c[:, :, 0].argmax()][0])

distance = np.sqrt( (right[0] - left[0])**2 + (right[1] - left[1])**2 )

x,y,w,h = cv2.boundingRect(c)

centx = np.sqrt( ((right[0] + left[0])**2)/4)
centy = np.sqrt( ((right[1] + left[1])**2)/4 )
print(centx, centy)

font = cv2.FONT_HERSHEY_SIMPLEX
cv2.circle(img, left, 5, (0, 0, 255), -1)
cv2.circle(img, right, 5, (0, 0, 255), -1)
cv2.circle(img, (int(centx), int(centy)), 5, (0, 0, 255), -1)
cv2.line(img, left, right, (255,0,0), 2)
cv2.drawContours(img, [c], -1, (0,255,0), 2)
cv2.rectangle(img,(x,y),(x+w,y+h),(0,255,0),2)
cv2.putText(img,'Distance: '+str(distance),(10,30), font, 1, (0,0,0),2, cv2.LINE_AA)
cv2.imshow('img', img)
cv2.imwrite('bulbresult.png', img)

结果:

enter image description here

关于python - 查找轮廓和边界以获取图像内部的点 OpenCV Python,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/51000056/

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