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)
的每个对象获取一个单独的列表- 外轮廓及其内轮廓的坐标。理想情况下,我想使用此列表在单独的空白 Canvas 上绘制对象(外部和内部轮廓)。
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('/image/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: Iteration of zero-sized operands is not enabled
最佳答案
那我也会回答这个问题。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)。
修改后的代码如下:
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('/image/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 Blob 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 的所有轮廓存储在
blob_cnts
中。 , 再次作为 (x, y)
的列表-坐标。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!
关于python - 找到带有孔的多个对象的轮廓,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/58970920/