How to extract only circular ROI portion of the image and show Radius of the circle with a button click in Tkinter window of Python OpenCV GUI

问题

Extract Circular ROI & Show Radius of the Circle in Tkinter Label

I am requesting help from python experts in this community. I have searched about my problem all over Stackexchange as well as the Github community. But I didn't find anything helpful. I have created a Tkinter GUI. In this GUI, I can upload my image from the destination folder. In Select of the evaluation section, I have written a script through which I can automatically view my ROI region in the circular part. The GUI is displayed at the bottom part of this question.

Help required Section: I am having trouble in creating a script through which:

1. when I click on Upload ROI button, only the selected ROI portion of the image gets saved at the destination folder i.e path = 'Data/images/' + name + '_' + method + ext
2. I can view the Radius of the circle somewhere on the the Tkinter GUI.

---

def ROI(self, image, method):
    if method == 'ROI':
        image = cv2.cvtColor(image, cv2.COLOR_RGB2GRAY)
        blimage = cv2.medianBlur(image, 15)
        circles = cv2.HoughCircles(blimage, cv2.HOUGH_GRADIENT, 1, 255, param1=100, param2=60, minRadius=0,
                                   maxRadius=0)

        if circles is not None:
            circles = np.uint16(np.around(circles))
            for i in circles[0, :]:
                cv2.circle(image, (i[0], i[1]), i[2], (0, 255, 0), 6)
                cv2.circle(image, (i[0], i[1]), 2, (0, 0, 255), 3)
        cv2.waitKey()

    else:
        print('method is wrong')

    return image

---

GUI

回答1:

UPDATE:

I added variable border to calculate x1,y1,x2,y2 so now it crops with borderline. Images show results for old code without border.

---

If you have only one circle (x,y,r) then you can use it to crop image

image = image[y-r:y+r, x-r:x+r]

I test it on some image with circle bigger then image and I had to use int16 instead of unit16 to get -1 instead of 65535 for 170-171 (y-r). Add I had to use min(), max()to get0instead-1`

def ROI(self, image, method):
    if method == 'ROI':
        image = cv2.cvtColor(image, cv2.COLOR_RGB2GRAY)
        blimage = cv2.medianBlur(image, 15)
        circles = cv2.HoughCircles(blimage, cv2.HOUGH_GRADIENT, 1, 255, param1=100, param2=60, minRadius=0,
                                   maxRadius=0)
        if circles is not None:
            #print(circles)

            # need `int` instead of `uint` to correctly calculate `y-r` (to get `-1` instead of `65535`)
            circles = np.int16(np.around(circles)) 

            for x,y,r in circles[0, :]:
                print('x, y, r:', x, y, r)

                border = 6

                cv2.circle(image, (x, y), r, (0, 255, 0), border)
                cv2.circle(image, (x, y), 2, (0, 0, 255), 3)

                height, width = image.shape
                print('height, width:', height, width)

                # calculate region to crop
                x1 = max(x-r - border//2, 0)      # eventually  -(border//2+1)
                x2 = min(x+r + border//2, width)  # eventually  +(border//2+1)
                y1 = max(y-r - border//2, 0)      # eventually  -(border//2+1)
                y2 = min(y+r + border//2, height) # eventually  +(border//2+1)
                print('x1, x2:', x1, x2)
                print('y1, y2:', y1, y2)

                # crop image 
                image = image[y1:y2,x1:x2]
                print('height, width:', image.shape)
    else:
        print('method is wrong')

    return image

For more circles you would have to first calculate region used for all circles (get drom all circles minimal values x-r,y-r and maximal values x+r,y+r) and next crop image.

Later I will try to use alpha channel to remove backgroud outside circle.

---

Image used for test (if someone else would like to test code)

---

EDIT: I added code which create black image with white circle to remove background.

def ROI(self, image, method):
    if method == 'ROI':
        image = cv2.cvtColor(image, cv2.COLOR_RGB2GRAY)
        blimage = cv2.medianBlur(image, 15)
        circles = cv2.HoughCircles(blimage, cv2.HOUGH_GRADIENT, 1, 255, param1=100, param2=60, minRadius=0,
                                   maxRadius=0)
        if circles is not None:
            print(circles)
            circles = np.int16(np.around(circles)) # need int instead of uint to correctly calculate y-r (to get -1 instead of 65535)
            for x,y,r in circles[0, :]:
                print('x, y, r:', x, y, r)
                height, width = image.shape
                print('height, width:', height, width)

                border = 6

                cv2.circle(image, (x, y), r, (0, 255, 0), border)
                cv2.circle(image, (x, y), 2, (0, 0, 255), 3)

                mask = np.zeros(image.shape, np.uint8) # black background
                cv2.circle(mask, (x, y), r, (255), border)  # white mask for black border
                cv2.circle(mask, (x, y), r, (255), -1) # white mask for (filled) circle
                #image = cv2.bitwise_and(image, mask)  # image with black background
                image = cv2.bitwise_or(image, ~mask)  # image with white background

                x1 = max(x-r - border//2, 0)      # eventually  -(border//2+1)
                x2 = min(x+r + border//2, width)  # eventually  +(border//2+1)
                y1 = max(y-r - border//2, 0)      # eventually  -(border//2+1)
                y2 = min(y+r + border//2, height) # eventually  +(border//2+1)
                print('x1, x2:', x1, x2)
                print('y1, y2:', y1, y2)

                image = image[y1:y2,x1:x2]
                print('height, width:', image.shape)
    else:
        print('method is wrong')

    return image

来源：https://stackoverflow.com/questions/59477313/how-to-extract-only-circular-roi-portion-of-the-image-and-show-radius-of-the-cir