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import cv2import imutilsimport numpy as npfrom scipy.spatial import distance as distfrom imutils import perspectiveimport pycurlimport jsonimport mathimport timeimport pymysqlcap = cv2.VideoCapture(0, cv2.CAP_DSHOW)URL = "http://127.0.0.1:5000/name"def midpoint(ptA, ptB):    return ((ptA[0] + ptB[0]) * 0.5, (ptA[1] + ptB[1]) * 0.5)def post_data(dict):    cor_num = pycurl.Curl()    cor_num.setopt(pycurl.URL, URL)    cor_num.setopt(pycurl.HTTPHEADER, ['Content-Type: application/json'])    # data = json.dumps({"name": "xgx", "sex": "male", "country": "china"})    data = json.dumps(dict)    cor_num.setopt(pycurl.POST, 1)    cor_num.setopt(pycurl.POSTFIELDS, data)    cor_num.setopt(pycurl.VERBOSE, 1)    cor_num.perform()    cor_num.close()host = 'localhost'port = 3306db = 'cap_testing'user = 'root'password = '123456'def get_connection():    conn = pymysql.connect(host=host, port=port, db=db, user=user, password=password)    return connppp = []iii = 1time_start = 0.0def detect_angle_demo(image):    global iii    global time_start    global stable_time    orig = image.copy()    # cimage = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)    cimage = cv2.GaussianBlur(image, (9, 9), 2, 2)    # RGB转HSV颜色空间    hsv = cv2.cvtColor(cimage, cv2.COLOR_BGR2HSV)    gray = cv2.cvtColor(cimage, cv2.COLOR_BGR2GRAY)    # 指定颜色的下限    lower_range = np.array([0, 43, 86])    # 指定颜色的上限    upper_range = np.array([10, 255, 255])    # 绿色区域    mask_g = cv2.inRange(hsv, (70, 43, 106), (80, 255, 255))    # 蓝色区域    mask_b = cv2.inRange(hsv, (110, 43, 126), (125, 255, 255))    mask_gb = {
   "green": mask_g, "blue": mask_b, }    eee = cv2.inRange(hsv, (0, 0, 0), (180, 255, 255))    # # 指定颜色的下限    # lower_range = np.array([27, 86, 6])    # # 指定颜色的上限    # upper_range = np.array([80, 255, 255])    # 提取特定颜色的区域    mask = cv2.inRange(hsv, lower_range, upper_range)    # mask = cv2.inRange(hsv, (36, 43, 46), (70, 255, 255))    mask2 = cv2.bitwise_not(mask)    edged = cv2.dilate(mask, None, iterations=2)    edged2 = cv2.erode(edged, None, iterations=2)    cv2.imshow("mask", edged2)    #cimage = cv2.GaussianBlur(cimage, (7, 7), 0)    contours, hierarchy = cv2.findContours(edged2, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)    # 寻找最大轮廓    areas = [cv2.contourArea(c) for c in contours]    # print(areas)    if len(areas) >= 1:        max_index = np.argmax(areas)        cnt = contours[max_index]        mianji = cv2.contourArea(cnt)        print(mianji)        # 得到最小方形区域，并得到方形区域的坐标        box = cv2.minAreaRect(cnt)        box = cv2.boxPoints(box)        box = np.array(box, dtype="int")        box = perspective.order_points(box)        (tl, tr, br, bl) = box        # cv2.drawContours(orig, [box.astype("int")], -1, (0, 255, 0), 2)        (centerX, centerY) = midpoint(tl, br)        # cv2.circle(orig, (int(centerX), int(centerY)), 3, (255, 0, 0), -1)        # cv2.circle(orig, (300, int(centerY)), 3, (0, 0, 255), -1)        (x1, y1), radius = cv2.minEnclosingCircle(cnt)  # 会返回一个二元组，第一个元素为圆心的坐标组成的元组，第二个元素为圆的半径值。        # cast to integers        center = (int(x1), int(y1))        radius = int(radius)        # draw the circle        cv2.circle(orig, center, radius, (0, 255, 0), 2)        # if (int(centerX) > 305):        #     passdata['index'] = 1        # elif (int(centerX) < 295):        #     passdata['index'] = 2        # else:        #     passdata['index'] = 0        # 计算图象上像素距离        # AB = dist.euclidean((centerX, centerY), (300, centerY))        # print("两点之间的像素距离是：", AB)        if mianji > 5000:            cv2.putText(orig, "The goal is existed", (20, 20), cv2.FONT_HERSHEY_SIMPLEX, 0.65,                        (0, 0, 0), 2)            circles = cv2.HoughCircles(gray, cv2.HOUGH_GRADIENT, 1.5, 30, param1=200, param2=120, minRadius=70, maxRadius=90)            # 整数化，#把circles包含的圆心和半径的值变成整数            #circles = np.uint16(np.around(circles))            if circles is not None:                for i in circles[0]:                    # 画出外边圆                    cv2.circle(orig, (i[0], i[1]), i[2], (0, 255, 0), 2)                    # 画出圆心                    cv2.circle(orig, (i[0], i[1]), 2, (0, 255, 0), 3)                    cv2.circle(orig, (300, i[1]), i[2], (0, 0, 255), 2)                    cv2.circle(orig, (300, i[1]), 2, (0, 0, 255), 3)                    x = int(i[0])                    y = i[1]                    r = i[2]                    if (x > 301):                        # passdata['index'] = 1   # 顺时针                        pass                    elif (x < 297):                        # passdata['index'] = 2                        pass                    else:                        # passdata['index'] = 0                        stable_time = stable_time + 1                    passdata['datax'] = x                    print(r)                    pixels = (39.8 / 2) / r                    err = pixels * (abs(x - 300))                    angle = math.asin(err/280)                    # print(3.14159*r*r)                    print(angle, err, pixels)                    if len(ppp) == 0:                        time_start = time.time()                        ppp.append(x)                    passdata['index'] = 5                    ppp.append(x)                    time_end = time.time()                    sum_t = time_end - time_start                    passdata['time'] = sum_t                    if stable_time == 50:                        passdata['index'] = 6                        passdata['stabletime'] = sum_t                    elif stable_time >= 51:                        passdata['index'] = 6                    sql = "INSERT INTO pages3 (X, Y, R, T, NUM) VALUES ('{0}','{1}', {2},{3},{4})".format(x, y, r, sum_t, iii)                    try:                        with conn.cursor() as cursor:                            cursor.execute(sql)                        conn.commit()                    except Exception as e:                        conn.rollback()                    iii = iii + 1                    # print(ppp[0], ppp[-1])                    # cv2.putText(orig, "{:.1f}mm".format(dt_mean),(int(x + 20), int(y + 20)), cv2.FONT_HERSHEY_SIMPLEX,0.65, (255, 255, 255), 2)            else:                # passdata['index'] = 0                print("未检测到圆")        else:            cv2.putText(orig, "The goal is not existed", (20, 20), cv2.FONT_HERSHEY_SIMPLEX, 0.65,                        (0, 0, 0), 2)            passdata['datax'] = 0            for key, value in mask_gb.items():                target = cv2.bitwise_and(eee, eee, mask=value)                cntss = cv2.findContours(target, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)[-2]                # cnts = cv2.findContours(value, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)                areas_big = [cv2.contourArea(c) for c in cntss]                if len(areas_big) >= 1:                    max_index_bg = np.argmax(areas_big)                    cnt_bg = cntss[max_index_bg]                    areasbg = cv2.contourArea(cnt_bg)                    if areasbg < 4000:                        continue                    else:                        print(key)                        if key == "green":                            # 发送逆时针转向信号                            passdata['direction'] = 2                        if key == "blue":                            # 发送顺时针转向信号                            passdata['direction'] = 1            passdata['index'] = 4        post_data(passdata)        cv2.imshow("circles", orig)        cv2.imshow("blue", mask_b)        cv2.imshow("green", mask_g)        #cv2.imshow("yuanshi", image)    else:        passdata['index'] = 4        print("未检测到物体")if __name__ == "__main__":    conn = get_connection()    cursor = conn.cursor(pymysql.cursors.DictCursor)    # cursor.execute("DROP TABLE IF EXISTS pages2")    # cursor.execute("CREATE TABLE pages3(id INT AUTO_INCREMENT PRIMARY KEY,X FLOAT ,Y FLOAT ,R FLOAT ,T FLOAT ,NUM INT, created TIMESTAMP DEFAULT CURRENT_TIMESTAMP)")    stable_time = 0    passdata = {
   'index': 6, 'direction': 1, 'time': 0}    while True:        ret, frame = cap.read()        frame = cv2.flip(frame, -1)        frame = imutils.resize(frame, width=600, height=600)        detect_angle_demo(frame)        # time_end = time.time()        # sum_t = time_end - time_start        # print("耗费时间", sum_t)        # if sum_t >= 60:        #     print("一分钟内检测的次数", iii)        #     break        # w, h = frame.shape        # if stable_time >= 50:        #     pass            # break        if cv2.waitKey(1) & 0xFF == ord('q'):            # passdata['datax'] = 300            passdata['index'] = 0            post_data(passdata)            cursor.close()            conn.close()            cap.release()            cv2.destroyAllWindows()            break

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