问题

I am trying to extract object from an image using the color using OpenCV, I have tried by inverse thresholding and grayscale combined with cv2.findContours() but I am unable to use it recursively. Furthermore I can't figure out how to "cut out" the match from the original image and save it to a single file.

EDIT

~
import cv2
import numpy as np

# load the images
empty = cv2.imread("empty.jpg")
full = cv2.imread("test.jpg")

# save color copy for visualization
full_c = full.copy()

# convert to grayscale
empty_g = cv2.cvtColor(empty, cv2.COLOR_BGR2GRAY)
full_g = cv2.cvtColor(full, cv2.COLOR_BGR2GRAY)

empty_g = cv2.GaussianBlur(empty_g, (51, 51), 0)
full_g = cv2.GaussianBlur(full_g, (51, 51), 0)
diff = full_g - empty_g

#  thresholding

diff_th = 
cv2.adaptiveThreshold(full_g,255,cv2.ADAPTIVE_THRESH_GAUSSIAN_C, 
cv2.THRESH_BINARY,11,2)

# combine the difference image and the inverse threshold
zone = cv2.bitwise_and(diff, diff_th, None)

# threshold to get the mask instead of gray pixels
_, zone = cv2.threshold(bag, 100, 255, 0)

# dilate to account for the blurring in the beginning
kernel = np.ones((15, 15), np.uint8)
bag = cv2.dilate(bag, kernel, iterations=1)

# find contours, sort and draw the biggest one
contours, _ = cv2.findContours(bag, cv2.RETR_TREE,
                              cv2.CHAIN_APPROX_SIMPLE)
contours = sorted(contours, key=cv2.contourArea, reverse=True)[:3]
i = 0
while i < len(contours):
    x, y, width, height = cv2.boundingRect(contours[i])
    roi = full_c[y:y+height, x:x+width]
    cv2.imwrite("piece"+str(i)+".png", roi)
    i += 1

Where empty is just a white image size 1500 * 1000 as the one above and test is the one above.

This is what I came up with, only downside, I have a third image instead of only the 2 expected showing a shadow zone now...

回答1:

Here's a simple approach:

Convert image to grayscale and Gaussian blur image
Perform canny edge detection
Dilate image to form a larger contour
Iterate through contours and find bounding boxes
Extract ROI and save image

Canny edge detection

Detected ROIs

To extract the ROI, you can find the bounding box coordinates using cv2.boundingRect(), crop the desired region, then save the image

x,y,w,h = cv2.boundingRect(c)
ROI = original[y:y+h, x:x+w]

First object

Second object

import cv2
import numpy as np

image = cv2.imread('1.jpg')
original = image.copy()
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
blurred = cv2.GaussianBlur(gray, (3, 3), 0)
canny = cv2.Canny(blurred, 120, 255, 1)
kernel = np.ones((5,5),np.uint8)
dilate = cv2.dilate(canny, kernel, iterations=1)

# Find contours
cnts = cv2.findContours(dilate, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
cnts = cnts[0] if len(cnts) == 2 else cnts[1]

# Iterate thorugh contours and filter for ROI
image_number = 0
for c in cnts:
    x,y,w,h = cv2.boundingRect(c)
    cv2.rectangle(image, (x, y), (x + w, y + h), (36,255,12), 2)
    ROI = original[y:y+h, x:x+w]
    cv2.imwrite("ROI_{}.png".format(image_number), ROI)
    image_number += 1

cv2.imshow('canny', canny)
cv2.imshow('image', image)
cv2.waitKey(0)

来源：https://stackoverflow.com/questions/56604151/python-extract-multiple-objects-from-image-opencv

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python