Question

我正在使用OpenCV来跟踪带有网络摄像头的镜头，我结合了在互联网上找到的两个脚本，但是现在我想拍摄一个png图像，并将其调整大小到所跟踪的圆的中心并缩放与边界圆跟踪成比例。

我尝试了崇高的机器人，胡须教程，但是我对感兴趣的区域和调整图像大小有些迷惑，任何帮助将不胜感激。

import numpy as np
import cv2
import time
import imutils
import math
import os

uniImg = cv2.imread('unicorn1.png')


def nothing(*arg):
        pass

cap = cv2.VideoCapture(0)
#Initial HSV GUI slider values to load on program start.
icol = (36, 202, 59, 71, 255, 255)    # Green
icol = (18, 0, 196, 36, 255, 255)  # Yellow
icol = (89, 0, 0, 125, 255, 255)  # Blue
icol = (0, 100, 80, 10, 255, 255)   # Red
icol = (104, 117, 222, 121, 255, 255)   # test
icol = (0, 0, 0, 255, 255, 255)   # New start
icol2 = (0, 0, 0, 255, 255, 20)   # New start
icol3 = (0, 0, 0, 255, 255, 20)   # New start

cv2.namedWindow('colorTest')
# Lower range colour sliders.
cv2.createTrackbar('lowHue', 'colorTest', icol[0], 255, nothing)
cv2.createTrackbar('lowSat', 'colorTest', icol[1], 255, nothing)
cv2.createTrackbar('lowVal', 'colorTest', icol[2], 255, nothing)
# Higher range colour sliders.
cv2.createTrackbar('highHue', 'colorTest', icol[3], 255, nothing)
cv2.createTrackbar('highSat', 'colorTest', icol[4], 255, nothing)
cv2.createTrackbar('highVal', 'colorTest', icol[5], 255, nothing)#
cv2.createTrackbar('erode','colorTest',icol2[5], 20, nothing)
cv2.createTrackbar('dilate','colorTest',icol3[5], 20, nothing)
while(1):
    timeCheck = time.time()

    lowHue = cv2.getTrackbarPos('lowHue', 'colorTest')
    lowSat = cv2.getTrackbarPos('lowSat', 'colorTest')
    lowVal = cv2.getTrackbarPos('lowVal', 'colorTest')
    highHue = cv2.getTrackbarPos('highHue', 'colorTest')
    highSat = cv2.getTrackbarPos('highSat', 'colorTest')
    highVal = cv2.getTrackbarPos('highVal', 'colorTest')
    erode = cv2.getTrackbarPos('erode', 'colorTest')
    dilate = cv2.getTrackbarPos('dilate', 'colorTest')

    _, frame = cap.read()
    hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)

    # Get HSV values from the GUI sliders.

    # define range of white color in HSV
    # change it according to your need !
    colorLow = np.array([lowHue,lowSat,lowVal])
    colorHigh = np.array([highHue,highSat,highVal])

    # Threshold the HSV image to get only white colors
    mask = cv2.inRange(hsv, colorLow, colorHigh)

    mask = cv2.erode(mask, None, iterations= erode)
    mask = cv2.dilate(mask, None, iterations= dilate)

    # Bitwise-AND mask and original image
    res = cv2.bitwise_and(frame,frame, mask= mask)


    # find contours in the mask and initialize the current
    # (x, y) center of the ball
    cnts = cv2.findContours(mask.copy(), cv2.RETR_EXTERNAL,
        cv2.CHAIN_APPROX_SIMPLE)
    cnts = cnts[0] if imutils.is_cv2() else cnts[1]
    center = None

    # only proceed if at least one contour was found
    if len(cnts) > 0:
        # find the largest contour in the mask, then use
        # it to compute the minimum enclosing circle and
        # centroid
        c = max(cnts, key=cv2.contourArea)
        ((x, y), radius) = cv2.minEnclosingCircle(c)
        M = cv2.moments(c)
        center = (int(M["m10"] / M["m00"]), int(M["m01"] / M["m00"]))

        # only proceed if the radius meets a minimum size
        if radius > 10:
            # draw the circle and centroid on the frame,
            # then update the list of tracked points
            cir = cv2.circle(frame, (int(x), int(y)), int(radius),
                (0, 255, 255), 2)


    cv2.imshow('frame',frame)
    cv2.imshow('mask',mask)
    cv2.imshow('res',res)

    k = cv2.waitKey(5) & 0xFF
    if k == 27:
        break

将PNG图像放置在跟踪球，OpenCV，Python中

0 个答案: