找到带有孔的多个对象的轮廓

Question

这是来自How to obtain boundary coordinates of binary mask with holes?的后续问题

给定相同的图像：

我想为(x, y)-外轮廓及其内轮廓的坐标的每个对象获取一个单独的列表。理想情况下，我想使用此列表在单独的空白画布上绘制对象（外轮廓和内轮廓）。

import matplotlib.pyplot as plt # For plotting
import cv2
from skimage import io         # Only needed for web grabbing images, use cv2.imread for local images


# Read image; find contours with hierarchy
blob = io.imread('https://i.stack.imgur.com/Ga5Pe.png')
contours, hier = cv2.findContours(blob, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)

# Define sufficient enough colors for blobs
colors = [(255, 0, 0), (0, 255, 0), (0, 0, 255)]

# Draw all contours, and their children, with different colors
out = cv2.cvtColor(blob, cv2.COLOR_GRAY2BGR)
# Check if it's the outer contour
k = -1
# Preallocate list
obj_list = []

for i, cnt in enumerate(contours):
    if (hier[0, i, 3] == -1):
        k += 1
    # cv2.drawContours(out, [cnt], -1, colors[k], 2)
    # Add contour list to object list if it is an inner contour
    obj_list.extend([cnt])

    # Concatenate array in list    
    obj_list = np.vstack(obj_list)    
    obj_list = np.squeeze(obj_list)   
    x = obj_list[:,0].tolist()    
    y = obj_list[:,1].tolist()


cv2.imshow('out', out)
cv2.waitKey(0)
cv2.destroyAllWindows()

编辑： 接受的答案仅适用于具有内部轮廓的对象，但不适用于没有内部轮廓的对象。我尝试通过添加以下代码来修复它：

# Add inner contours of blob to list
cnt_idx = np.squeeze(np.where(hier[0, :, 3] == b_idx))
c_cnt_idx = np.array(cnt_idx)
if c_cnt_idx.size > 0:
    cnt_idx = b_idx

但我收到以下错误消息：

ValueError：未启用零大小操作数的迭代

Answer 1

那我也来回答一下这个问题。同样，我跳过了整个绘图部分。而且，正如我之前的回答中所建议的，我修改了 blob 的发现，以便使用 NumPy 预先找到正确的“blob 索引”（相对于层次结构）。

修改后的代码来了：

import cv2
import numpy as np
from skimage import io         # Only needed for web grabbing images, use cv2.imread for local images

# Read image; add an additional hole; find contours with hierarchy
blob = io.imread('https://i.stack.imgur.com/Ga5Pe.png')
cv2.circle(blob, (380, 120), 25, 0, cv2.FILLED)
contours, hier = cv2.findContours(blob, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)

# Define sufficient enough colors for blobs
colors = [(255, 0, 0), (0, 255, 0), (0, 0, 255)]

# Get blob indices with respect to hierarchy
blob_idx = np.squeeze(np.where(hier[0, :, 3] == -1))

# Initialize blob images
blob_imgs = []

# Iterate all blobs
k = 0
for b_idx in np.nditer(blob_idx):

    # Add outer contour of blob to list
    blob_cnts = [contours[b_idx]]

    # Add inner contours of blob to list, if present
    cnt_idx = np.squeeze(np.where(hier[0, :, 3] == b_idx))
    if (cnt_idx.size > 0):
        blob_cnts.extend([contours[c_idx] for c_idx in np.nditer(cnt_idx)])

    # Generate blank BGR image with same size as input; draw contours
    img = np.zeros((blob.shape[0], blob.shape[1], 3), np.uint8)
    cv2.drawContours(img, blob_cnts, -1, colors[k], 2)
    blob_imgs.append(img)
    k += 1

# Just for visualization: Iterate all blob images
k = 0
for img in blob_imgs:
    cv2.imshow(str(k), img)
    k += 1
cv2.waitKey(0)
cv2.destroyAllWindows()

生成的两个输出（我在其中一个斑点中添加了另一个孔以检查多个内部轮廓）：

因此，在主循环中，您现在将属于一个 blob 的所有轮廓都存储在 blob_cnts 中，同样作为 (x, y) 坐标列表。因此，您可以生成绘图或做任何您喜欢的事情，而不是生成此处显示的不同图像。

希望有帮助！