Question

我已经编写了一个代码，可以通过使用HSV颜色代码来检测MCB的尺寸。但是，当我运行程序时，我达到了预期的输出，但是在检测到的对象周围还有3个其他帧。虽然输出文本数据设置为一帧，但我仍然无法漫游其他3个无意义的帧。我想问一下如何删除它们的任何建议。

我设置轮廓数据以检测HSV代码的最大区域，但仍然无法正常工作。

为获得更好的主意，我将附上代码提供的屏幕截图。

输出图像

代码如下：

import cv2
from collections import deque
from scipy.spatial import distance as dist
from imutils import perspective
import numpy as np
import argparse
import imutils
import math
import time

font = cv2.FONT_HERSHEY_SIMPLEX

def midpoint(ptA, ptB):
    return ((ptA[0] + ptB[0]) * 0.5, (ptA[1] + ptB[1]) * 0.5)

ap = argparse.ArgumentParser()
ap.add_argument("-v", "--video", help="path to the (optional) video file")
args = vars(ap.parse_args())

sensitivity = 43
greyLower = np.array([96,0,176-sensitivity])
greyUpper = np.array([180,sensitivity,255])
pixelsPerMetric = None
KNOWN_WIDTH = 19

if not args.get("video", False):
    camera = cv2.VideoCapture(0)
else:
    camera = cv2.VideoCapture(args["video"])

while True:
    (grabbed, frame) = camera.read()

    if args.get("video") and not grabbed:
        break

    frame = imutils.resize(frame, width=600)
    hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)

    mask = cv2.inRange(hsv,greyLower, greyUpper)
    mask = cv2.erode(mask, None, iterations=2)
    mask = cv2.dilate(mask, None, iterations=2)

    (_, contours, hierarchy) = cv2.findContours(mask.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
    center = None
    for pic, contour in enumerate(contours):

        if len(contours) > 0:
            contour = max(contours, key =cv2.contourArea)
            x,y,w,h = cv2.boundingRect(contour)
            rect = (x+w, y+h)
            rect = cv2.minAreaRect(contour)
            box = cv2.boxPoints(rect)
            box = np.int0(box)
            box = perspective.order_points(box)
            M = cv2.moments(contour)
            for (x, y) in box:
                M = cv2.rectangle(frame,(int(x),int(y)),(int(x+w), int(y+h)),(0,0,139),2)
            # unpack the ordered bounding box, then compute the midpoint
            # between the top-left and top-right coordinates, followed by
            # the midpoint between bottom-left and bottom-right coordinates
            (tl, tr, br, bl) = box
            (tltrX, tltrY) = midpoint(tl, tr)
            (blbrX, blbrY) = midpoint(bl, br)

            # compute the midpoint between the top-left and top-right points,
            # followed by the midpoint between the top-righ and bottom-right
            (tlblX, tlblY) = midpoint(tl, bl)
            (trbrX, trbrY) = midpoint(tr, br)

            # draw the midpoints on the image
            cv2.circle(M, (int(tltrX), int(tltrY)), 5, (255, 0, 0), -1)
            cv2.circle(M, (int(blbrX), int(blbrY)), 5, (255, 0, 0), -1)
            cv2.circle(M, (int(tlblX), int(tlblY)), 5, (255, 0, 0), -1)
            cv2.circle(M, (int(trbrX), int(trbrY)), 5, (255, 0, 0), -1)

            # draw lines between the midpoints
            cv2.line(M, (int(tltrX), int(tltrY)), (int(blbrX), int(blbrY)),
                    (255, 0, 255), 2)
            cv2.line(M, (int(tlblX), int(tlblY)), (int(trbrX), int(trbrY)),
                    (255, 0, 255), 2)
            # compute the Euclidean distance between the midpoints
            dA = dist.euclidean((tltrX, tltrY), (blbrX, blbrY))
            dB = dist.euclidean((tlblX, tlblY), (trbrX, trbrY))

            # if the pixels per metric has not been initialized, then
            # compute it as the ratio of pixels to supplied metric
            # (in this case, inches)

            # compute the size of the object
            dimA = dA / KNOWN_WIDTH
            dimB = dB / KNOWN_WIDTH

            if rect >300:
                    frame = cv2.rectangle(frame,(int(x),int(y)),(int(x+w), int(y+h)),(0,0,139),2)
                    cv2.putText(frame,"MCB",(x,y),cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0,0,139))

            # draw the object sizes on the image
            cv2.putText(frame, "{:.1f}cm".format(dimA),
                    (int(tltrX - 15), int(tltrY - 10)), cv2.FONT_HERSHEY_SIMPLEX,
                    0.65, (255, 255, 255), 2)
            cv2.putText(frame, "{:.1f}cm".format(dimB),
                    (int(trbrX + 10), int(trbrY)), cv2.FONT_HERSHEY_SIMPLEX,
                    0.65, (255, 255, 255), 2)
    cv2.imshow("Frame", frame)

    key = cv2.waitKey(10) & 0xFF

    if key == ord("q"):
        break

camera.release()
cv2.destroyAllWindows()

任何建议都将对您有所帮助，在此先感谢您！

检测活动物体时如何删除多个帧

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