Question

我正在尝试运行在python中使用opencv编写的脚本，该脚本使用网络摄像头来跟踪彩色对象（这里的对象是蓝色的），这在opencv的文档中也有提及here

import cv2
import numpy as np

cap = cv2.VideoCapture(0)

while(1):

    # Take each frame
    _, frame = cap.read()

    # Convert BGR to HSV
    hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)

    # define range of blue color in HSV
    lower_blue = np.array([110,50,50])
    upper_blue = np.array([130,255,255])

    # Threshold the HSV image to get only blue colors
    mask = cv2.inRange(hsv, lower_blue, upper_blue)

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

    cv2.imshow('frame',frame)
    cv2.imshow('mask',mask)
    cv2.imshow('res',res)
    k = cv2.waitKey(5) & 0xFF
    if k == 27:
        break

cv2.destroyAllWindows()

但是这段代码会产生错误：

OpenCV Error: Sizes of input arguments do not match (The lower bounary is neither an      array of the same size and same type as src, nor a scalar) in inRange, file     /build/buildd/opencv-2.4.2+dfsg/modules/core/src/arithm.cpp, line 2527
Traceback (most recent call last):
File "blue.py", line 19, in <module>
mask = cv2.inRange(hsv, lower_blue, upper_blue)
cv2.error: /build/buildd/opencv-2.4.2+dfsg/modules/core/src/arithm.cpp:2527: error: (     (-209) The lower bounary is neither an array of the same size and same type as src, nor a scalar in function inRange

我尝试过相关的stackoverflow问题中提供的解决方案，但没有一个有用。代码有什么问题？为什么会出现这个错误？

我正在使用opencv 2.4.2＆amp; ubuntu上的python 2.7

Answer 1

HSV中的蓝色范围应为：

lower_blue = np.array([110, 50, 50], dtype=np.uint8)
upper_blue = np.array([130,255,255], dtype=np.uint8)

Answer 2

这是一个HSV颜色阈值脚本，用于确定上下范围，而不是猜测和检查

import cv2
import sys
import numpy as np

def nothing(x):
    pass

# Load in image
image = cv2.imread('1.png')

# Create a window
cv2.namedWindow('image')

# create trackbars for color change
cv2.createTrackbar('HMin','image',0,179,nothing) # Hue is from 0-179 for Opencv
cv2.createTrackbar('SMin','image',0,255,nothing)
cv2.createTrackbar('VMin','image',0,255,nothing)
cv2.createTrackbar('HMax','image',0,179,nothing)
cv2.createTrackbar('SMax','image',0,255,nothing)
cv2.createTrackbar('VMax','image',0,255,nothing)

# Set default value for MAX HSV trackbars.
cv2.setTrackbarPos('HMax', 'image', 179)
cv2.setTrackbarPos('SMax', 'image', 255)
cv2.setTrackbarPos('VMax', 'image', 255)

# Initialize to check if HSV min/max value changes
hMin = sMin = vMin = hMax = sMax = vMax = 0
phMin = psMin = pvMin = phMax = psMax = pvMax = 0

output = image
wait_time = 33

while(1):

    # get current positions of all trackbars
    hMin = cv2.getTrackbarPos('HMin','image')
    sMin = cv2.getTrackbarPos('SMin','image')
    vMin = cv2.getTrackbarPos('VMin','image')

    hMax = cv2.getTrackbarPos('HMax','image')
    sMax = cv2.getTrackbarPos('SMax','image')
    vMax = cv2.getTrackbarPos('VMax','image')

    # Set minimum and max HSV values to display
    lower = np.array([hMin, sMin, vMin])
    upper = np.array([hMax, sMax, vMax])

    # Create HSV Image and threshold into a range.
    hsv = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)
    mask = cv2.inRange(hsv, lower, upper)
    output = cv2.bitwise_and(image,image, mask= mask)

    # Print if there is a change in HSV value
    if( (phMin != hMin) | (psMin != sMin) | (pvMin != vMin) | (phMax != hMax) | (psMax != sMax) | (pvMax != vMax) ):
        print("(hMin = %d , sMin = %d, vMin = %d), (hMax = %d , sMax = %d, vMax = %d)" % (hMin , sMin , vMin, hMax, sMax , vMax))
        phMin = hMin
        psMin = sMin
        pvMin = vMin
        phMax = hMax
        psMax = sMax
        pvMax = vMax

    # Display output image
    cv2.imshow('image',output)

    # Wait longer to prevent freeze for videos.
    if cv2.waitKey(wait_time) & 0xFF == ord('q'):
        break

cv2.destroyAllWindows()

Answer 3

为了在OpenCV-python中基于颜色检测对象，我认为此存储库将帮助您检查此GitHub存储库：

https://github.com/shashiben/Opencv/blob/master/Object%20Detection/object_detect_with_hsv.py

我确实使用跟踪栏根据HSV颜色跟踪了对象

使用opencv python进行颜色检测

3 个答案: