Python NumPy/OpenCV 2：如何裁剪非矩形区域？
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NumPy/OpenCV 2: how do I crop non-rectangular region?
提问by ffriend
I have a set of points that make a shape(closed polyline). Now I want to copy/crop all pixels from some image inside this shape, leaving the rest black/transparent. How do I do this?
我有一组形成形状的点（闭合折线）。现在我想从这个形状内的某个图像复制/裁剪所有像素，剩下的黑色/透明。我该怎么做呢？
For example, I have this:
例如，我有这个：
and I want to get this:
我想得到这个：
采纳答案by KobeJohn
*edit - updated to work with images that have an alpha channel.
*edit - 更新以处理具有 Alpha 通道的图像。
This worked for me:
这对我有用：
- Make a mask with all black (all masked)
- Fill a polygon with white in the shape of your ROI
- combine the mask and your image to get the ROI with black everywhere else
- 做一个全黑的面具（全部蒙面）
- 以 ROI 的形状用白色填充多边形
- 将蒙版和您的图像结合起来，以在其他地方获得黑色的 ROI
You probably just want to keep the image and mask separate for functions that accept masks. However, I believe this does what you specifically asked for:
对于接受掩码的函数，您可能只想将图像和掩码分开。但是，我相信这可以满足您的具体要求：
import cv2
import numpy as np
# original image
# -1 loads as-is so if it will be 3 or 4 channel as the original
image = cv2.imread('image.png', -1)
# mask defaulting to black for 3-channel and transparent for 4-channel
# (of course replace corners with yours)
mask = np.zeros(image.shape, dtype=np.uint8)
roi_corners = np.array([[(10,10), (300,300), (10,300)]], dtype=np.int32)
# fill the ROI so it doesn't get wiped out when the mask is applied
channel_count = image.shape[2] # i.e. 3 or 4 depending on your image
ignore_mask_color = (255,)*channel_count
cv2.fillPoly(mask, roi_corners, ignore_mask_color)
# from Masterfool: use cv2.fillConvexPoly if you know it's convex
# apply the mask
masked_image = cv2.bitwise_and(image, mask)
# save the result
cv2.imwrite('image_masked.png', masked_image)
回答by Kanish Mathew
The following code would be helpful for cropping the images and get them in a white background.
以下代码将有助于裁剪图像并将它们置于白色背景中。
import cv2
import numpy as np
# load the image
image_path = 'input image path'
image = cv2.imread(image_path)
# create a mask with white pixels
mask = np.ones(image.shape, dtype=np.uint8)
mask.fill(255)
# points to be cropped
roi_corners = np.array([[(0, 300), (1880, 300), (1880, 400), (0, 400)]], dtype=np.int32)
# fill the ROI into the mask
cv2.fillPoly(mask, roi_corners, 0)
# The mask image
cv2.imwrite('image_masked.png', mask)
# applying th mask to original image
masked_image = cv2.bitwise_or(image, mask)
# The resultant image
cv2.imwrite('new_masked_image.png', masked_image)
Input Image:
输入图像：
Mask Image:
面具图片：
Resultant output image:
结果输出图像：
