如何删除 python 中的图像背景
how to remove background of images in python
我有一个包含全幅人物图像的数据集我想删除这些图像中的所有背景,只留下全幅人物,
我的问题:
是否有任何 python 代码可以做到这一点?
我需要每次都指定人物对象的坐标吗?
这是使用 Python/OpenCV 的一种方法。
- 读取输入
- 转换为灰色
- 阈值并反转为掩码
- 可选择应用形态学来清除任何无关的点
- 消除边缘锯齿
- 将输入的副本转换为 BGRA 并将掩码作为 alpha 通道插入
- 保存结果
输入:
import cv2
import numpy as np
# load image
img = cv2.imread('person.png')
# convert to graky
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
# threshold input image as mask
mask = cv2.threshold(gray, 250, 255, cv2.THRESH_BINARY)[1]
# negate mask
mask = 255 - mask
# apply morphology to remove isolated extraneous noise
# use borderconstant of black since foreground touches the edges
kernel = np.ones((3,3), np.uint8)
mask = cv2.morphologyEx(mask, cv2.MORPH_OPEN, kernel)
mask = cv2.morphologyEx(mask, cv2.MORPH_CLOSE, kernel)
# anti-alias the mask -- blur then stretch
# blur alpha channel
mask = cv2.GaussianBlur(mask, (0,0), sigmaX=2, sigmaY=2, borderType = cv2.BORDER_DEFAULT)
# linear stretch so that 127.5 goes to 0, but 255 stays 255
mask = (2*(mask.astype(np.float32))-255.0).clip(0,255).astype(np.uint8)
# put mask into alpha channel
result = img.copy()
result = cv2.cvtColor(result, cv2.COLOR_BGR2BGRA)
result[:, :, 3] = mask
# save resulting masked image
cv2.imwrite('person_transp_bckgrnd.png', result)
# display result, though it won't show transparency
cv2.imshow("INPUT", img)
cv2.imshow("GRAY", gray)
cv2.imshow("MASK", mask)
cv2.imshow("RESULT", result)
cv2.waitKey(0)
cv2.destroyAllWindows()
透明结果:
我有一个包含全幅人物图像的数据集我想删除这些图像中的所有背景,只留下全幅人物,
我的问题:
是否有任何 python 代码可以做到这一点?
我需要每次都指定人物对象的坐标吗?
这是使用 Python/OpenCV 的一种方法。
- 读取输入
- 转换为灰色
- 阈值并反转为掩码
- 可选择应用形态学来清除任何无关的点
- 消除边缘锯齿
- 将输入的副本转换为 BGRA 并将掩码作为 alpha 通道插入
- 保存结果
输入:
import cv2
import numpy as np
# load image
img = cv2.imread('person.png')
# convert to graky
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
# threshold input image as mask
mask = cv2.threshold(gray, 250, 255, cv2.THRESH_BINARY)[1]
# negate mask
mask = 255 - mask
# apply morphology to remove isolated extraneous noise
# use borderconstant of black since foreground touches the edges
kernel = np.ones((3,3), np.uint8)
mask = cv2.morphologyEx(mask, cv2.MORPH_OPEN, kernel)
mask = cv2.morphologyEx(mask, cv2.MORPH_CLOSE, kernel)
# anti-alias the mask -- blur then stretch
# blur alpha channel
mask = cv2.GaussianBlur(mask, (0,0), sigmaX=2, sigmaY=2, borderType = cv2.BORDER_DEFAULT)
# linear stretch so that 127.5 goes to 0, but 255 stays 255
mask = (2*(mask.astype(np.float32))-255.0).clip(0,255).astype(np.uint8)
# put mask into alpha channel
result = img.copy()
result = cv2.cvtColor(result, cv2.COLOR_BGR2BGRA)
result[:, :, 3] = mask
# save resulting masked image
cv2.imwrite('person_transp_bckgrnd.png', result)
# display result, though it won't show transparency
cv2.imshow("INPUT", img)
cv2.imshow("GRAY", gray)
cv2.imshow("MASK", mask)
cv2.imshow("RESULT", result)
cv2.waitKey(0)
cv2.destroyAllWindows()
透明结果: