如何使用OpenCV去除图片的背景？

Question

从这张照片中删除背景的最好方法是什么？

​

​

我试着转换成单纯疱疹病毒，并使用inRange获得一个面具，但它不能完全吸收植物，并包括一些灰浆之间的砖块。

Answer 1

由于所需植物和背景之间似乎有明显的区别，我建议使用具有较低和较高阈值范围的颜色阈值来隔离所需区域。其思想是将图像转换为HSV格式，颜色阈值以获得掩码，然后按位and。我认为你有正确的方法，但在确定下限和上限时遇到了麻烦。使用此下限/上限范围：

hsv_lower = np.array([41,57,78])
hsv_upper = np.array([145,255,255])

​

​

import cv2
import numpy as np

image = cv2.imread("1.jpg")
original = image.copy()
hsv = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)

hsv_lower = np.array([41,57,78])
hsv_upper = np.array([145,255,255])
mask = cv2.inRange(hsv, hsv_lower, hsv_upper)
result = cv2.bitwise_and(original, original, mask=mask)

cv2.imshow('mask', mask)
cv2.imshow('result', result)
cv2.waitKey()

要确定下限和上限范围，我们可以使用颜色阈值HSV脚本

import cv2
import sys
import numpy as np

def nothing(x):
    pass

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

# 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()