python - 删除轮廓 OpenCV

Question

我的形象

我想得到

https://ibb.co/t8hNkM2

我只能得到

我能够找到最大轮廓

def img_counter_max(image_file: str):
    img = cv2.imread(image_file)
    # grayscale
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)  # меняем цветовую модель с BGR на HSV
    cv2.waitKey(0)
    # binarize
    ret, thresh = cv2.threshold(gray, 127, 255, cv2.THRESH_BINARY_INV)
    cv2.waitKey(0)
    # find contours
    ctrs, hier = cv2.findContours(thresh.copy(), cv2.RETR_TREE, cv2.CHAIN_APPROX_NONE)
    # sort contours
    sorted_ctrs = sorted(ctrs, key=lambda ctr: cv2.boundingRect(ctr)[0])
    # sorted_ctrs sorted(ctrs, key=cv2.contourArea, reverse=True)[0]
    contour_sizes = [(cv2.contourArea(contour), contour) for contour in sorted_ctrs]
    biggest_contour = max(contour_sizes, key=lambda x: x[0])[1]
    x, y, w, h = cv2.boundingRect(biggest_contour)
    roi = img[y:y + h, x:x + w]
    cv2.imwrite("C:\\Users\\dennn\\PycharmProjects\\untitled2\\imag\\roi1.jpg", 
    roi)
    cv2.rectangle(img, (x, y), (x + w, y + h), (90, 255, 0), 2)
    from tensorflow.python import Size
    resize_img = cv2.resize(img, (512,512))
    # cv2.resize(img, Size(512,512), interpolation=cv2.INTER_AREA)
    cv2.namedWindow("Display frame", cv2.WINDOW_AUTOSIZE);
    cv2.imshow('Display frame', resize_img)
    cv2.waitKey(0)

如何获得我需要的图像？

标签： pythonopencv

Answer 1

我发现排序依据contourArea()给出了错误的结果。可能它会计算轮廓内的所有点，但不计算它使用的矩形区域 - 这个矩形可以更大。

我boundingRect()用来获取轮廓使用的矩形，然后使用计算大小w*h，然后以正确的方式对轮廓进行排序。

我使用for-loop 来显示具有不同矩形的图像，并查看哪个轮廓给出了预期的区域。通过这种方式，我看到第三个轮廓给出了预期的区域，因此我可以使用[2]它来获取并保存它。

---

最终我会使用大小来选择w*h在某个范围内的区域

expecte_region_size - range < w*h < expecte_region_size + range

---

最终我会使用for-loop 来显示具有不同矩形的图像来手动选择要使用哪个矩形保存在文件中。

---

import cv2

img = cv2.imread('image.jpg')

# grayscale
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)  # меняем цветовую модель с BGR на HSV

# binarize
ret, thresh = cv2.threshold(gray, 127, 255, cv2.THRESH_BINARY_INV)

# find contours
ctrs, hier = cv2.findContours(thresh.copy(), cv2.RETR_TREE, cv2.CHAIN_APPROX_NONE)

# find rect and area - and create items [contour, rect, area] - but sorting by area gives wrong results
#items = [[ctr, cv2.boundingRect(ctr), cv2.contourArea(ctr)] for ctr in ctrs]

# find rect - and create items [contour, rect]
items = [[ctr, cv2.boundingRect(ctr)] for ctr in ctrs]

# find rect's size and create items [contour, rect, size]
items = [[ctr, rect, rect[2]*rect[3]] for ctr, rect in items]

# sort by size 
items = sorted(items, key=lambda x: x[2], reverse=True)

for index, item in enumerate(items[:5]):

    contour = item[0]
    x, y, w, h = item[1]
    size = item[2]

    print(index, '->', size, '(', x, y, w, h, ')')

    img_copy = img.copy()
    cv2.rectangle(img_copy, (x, y), (x + w, y + h), (0, 0, 255), 15)
    resize_img = cv2.resize(img_copy, (512,512))

    cv2.imshow('frame', resize_img)
    cv2.waitKey(0)

cv2.destroyAllWindows()

# --- save image ---

item = items[2]

contour = item[0]
x, y, w, h = item[1]
size = item[2]

img = img[y:y+h, x:x+w]
cv2.imwrite('output.jpg', img)

预习：

输出：