Python从图像opencv中提取多个对象

Question

我正在尝试使用 OpenCV 使用颜色从图像中提取对象，我尝试过将逆阈值和灰度结合使用，cv2.findContours()但我无法递归使用它。此外，我无法弄清楚如何从原始图像中“剪切”匹配并将其保存到单个文件中。

编辑

~
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

其中 empty 只是一个白色图像大小 1500 * 1000 如上图和 test 是上图。

这就是我想出的，唯一的缺点是，我有第三张图像，而不是现在预期的 2 张显示阴影区域......

Answer 1

这是一个简单的方法：

• 将图像转换为灰度和高斯模糊图像
• 执行精明的边缘检测
• 扩大图像以形成更大的轮廓
• 遍历轮廓并找到边界框
• 提取 ROI 并保存图像

Canny 边缘检测

检测到的投资回报率

要提取 ROI，您可以使用 找到边界框坐标cv2.boundingRect()，裁剪所需区域，然后保存图像

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

第一个对象

第二个对象

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)