python opencv 打开相机检测圆点

 原图

 结果

# coding:utf-8
import cv2
import numpy as np
import matplotlib.pyplot as plt


def mainFigure(img):
    w = 20
    h = 5
    params = cv2.SimpleBlobDetector_Params()
    # Setup SimpleBlobDetector parameters.
    # print('params')
    # print(params)
    # print(type(params))


    # Filter by Area.
    params.filterByArea = True
    params.minArea = 10e1
    params.maxArea = 10e3
    params.minDistBetweenBlobs = 25
    # params.filterByColor = True
    params.filterByConvexity = False
    # tweak these as you see fit
    # Filter by Circularity
    # params.filterByCircularity = False
    # params.minCircularity = 0.2
    # params.blobColor = 0
    # # # Filter by Convexity
    # params.filterByConvexity = True
    # params.minConvexity = 0.87
    # Filter by Inertia
    # params.filterByInertia = True
    # params.filterByInertia = False
    # params.minInertiaRatio = 0.01


    gray= cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
    # Detect blobs.
    # image = cv2.resize(gray_img, (int(img.shape[1]/4),int(img.shape[0]/4)), 1, 1, cv2.INTER_LINEAR)
    # image = cv2.resize(gray_img, dsize=None, fx=0.25, fy=0.25, interpolation=cv2.INTER_LINEAR)
    minThreshValue = 120
    _, gray = cv2.threshold(gray, minThreshValue, 255, cv2.THRESH_BINARY)
    gray = cv2.resize(gray, dsize=None, fx=2, fy=2, interpolation=cv2.INTER_LINEAR)
    # plt.imshow(gray)
    # cv2.imshow("gray",gray)

    detector = cv2.SimpleBlobDetector_create(params)
    keypoints = detector.detect(gray)

    print(len(keypoints))


    fig = plt.figure()
    # opencv
    im_with_keypoints = cv2.drawKeypoints(gray, keypoints, np.array([]), (255, 0, 0), cv2.DRAW_MATCHES_FLAGS_DRAW_RICH_KEYPOINTS)
    # plt
    # im_with_keypoints = cv2.drawKeypoints(gray, keypoints, np.array([]), (0, 0, 255),  cv2.DRAW_MATCHES_FLAGS_DRAW_RICH_KEYPOINTS)
    color_img = cv2.cvtColor(im_with_keypoints, cv2.COLOR_BGR2RGB)

    # plt.imshow(color_img,interpolation='bicubic')
    # fname = "key points"
    # titlestr = '%s found %d keypoints' % (fname, len(keypoints))
    # plt.title(titlestr)
    # fig.canvas.set_window_title(titlestr)
    # plt.show()

    cv2.imshow('findCorners', color_img)
    cv2.waitKey()


def main(img, fig):

    params = cv2.SimpleBlobDetector_Params()
    # Filter by Area.
    params.filterByArea = True
    params.minArea = 10e1
    params.maxArea = 10e3
    params.minDistBetweenBlobs = 25
    # params.filterByColor = True
    params.filterByConvexity = False
    # tweak these as you see fit
    # Filter by Circularity
    # params.filterByCircularity = False
    # params.minCircularity = 0.2
    # params.blobColor = 0
    # # # Filter by Convexity
    # params.filterByConvexity = True
    # params.minConvexity = 0.87
    # Filter by Inertia
    # params.filterByInertia = True
    # params.filterByInertia = False
    # params.minInertiaRatio = 0.01


    gray= cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
    # Detect blobs.
    # cv2.imshow('findCorners', img)
    # cv2.waitKey(1)
    minThreshValue = 120
    _, gray = cv2.threshold(gray, minThreshValue, 255, cv2.THRESH_BINARY)
    gray = cv2.resize(gray, dsize=None, fx=2, fy=2, interpolation=cv2.INTER_LINEAR)
    # plt.imshow(gray)
    # cv2.imshow("gray",gray)

    detector = cv2.SimpleBlobDetector_create(params)
    keypoints = detector.detect(gray)

    if keypoints is not None:
        # print(len(keypoints))

        # opencv
        im_with_keypoints = cv2.drawKeypoints(gray, keypoints, np.array([]), (255, 0, 0), cv2.DRAW_MATCHES_FLAGS_DRAW_RICH_KEYPOINTS)
        # plt
        # im_with_keypoints = cv2.drawKeypoints(gray, keypoints, np.array([]), (0, 0, 255),  cv2.DRAW_MATCHES_FLAGS_DRAW_RICH_KEYPOINTS)

        color_img = cv2.cvtColor(im_with_keypoints, cv2.COLOR_BGR2RGB)


        # # plt
        # fname = "key points"
        # titlestr = '%s found %d keypoints' % (fname, len(keypoints))
        # fig.canvas.set_window_title(titlestr)
        # plt.title(titlestr)
        # # plt.show()
        # plt.imshow(color_img)
        # plt.pause(0.1)
        # fig.clf()

        # opencv
        if len(keypoints) > 200:
            cv2.putText(color_img, ("circles num = % d" % len(keypoints)), (50, 50),
                        cv2.FONT_HERSHEY_SIMPLEX, 1, (255, 0, 0), 2)
        else:
            cv2.putText(color_img, ("Notice: % s" % "Change Position"), (50, 50),
                        cv2.FONT_HERSHEY_SIMPLEX, 1, (255, 0, 0), 2)

        cv2.imshow('findCorners', color_img)
        cv2.waitKey(1)



if __name__ == "__main__":

    # 图片测试
    # # img = cv2.imread("circles/circels.jpg",1)
    img = cv2.imread("circles/Snap_001.jpg",1)
    mainFigure(img)


    # # # 打开相机
    # capture = cv2.VideoCapture(0)
    # print("hello world")
    #
    # fig = plt.figure()
    # # plt.ion()
    #
    # if capture is None:
    #     print("Fail to open camera")
    # else:
    #     while (True):
    #         # 获取一帧
    #         ret, frame = capture.read()
    #
    #         if frame is None:
    #             print("Fail to grab")
    #             continue
    #         else:
    #             # 将这帧转换为灰度图
    #             # gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
    #             main(frame, fig)
    #         # cv2.imshow('frame', frame)
    #         key = cv2.waitKey(1)
    #         if key == ord('q'):
    #             break