5

我有白色背景的标志（任意形状的标志）图像，我想获得透明背景的标志图像。

我设法创建了一个蒙版并将其应用于图像，并认为使蒙版透明是可行的。我在这里和其他地方搜索了很多，但没有什么真正帮助我。

import cv2
import numpy as np

file_name = "/path/to/input/img/Unbenannt.jpg" # can be also .png

img = cv2.imread(file_name)

gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
th, threshed = cv2.threshold(gray, 240, 255, cv2.THRESH_BINARY_INV)

kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (11,11))
morphed = cv2.morphologyEx(threshed, cv2.MORPH_CLOSE, kernel)

_, roi, _ = cv2.findContours(morphed, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)

mask = np.zeros(img.shape, img.dtype)

cv2.fillPoly(mask, roi, (255,)*img.shape[2], )

masked_image = cv2.bitwise_and(img, mask)

cv2.imwrite("/path/to/output/mask_test.png", masked_image)

输入：

在此处输入图像描述

电流输出：

在此处输入图像描述

如前所述，我想让背景透明。

高度赞赏帮助。

4

2 回答 2

4

我发现我必须将图像转换为 BGRA 才能获得透明背景。我还添加了一种将图像剪切到其边界矩形的方法。正如所承诺的，工作代码：

import cv2
import numpy as np

file_name = "/path/to/img.png"

def cut(img):
  # crop image
  gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
  th, threshed = cv2.threshold(gray, 240, 255, cv2.THRESH_BINARY_INV)

  kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (11,11))
  morphed = cv2.morphologyEx(threshed, cv2.MORPH_CLOSE, kernel)

  _, cnts, _ = cv2.findContours(morphed, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
  cnt = sorted(cnts, key=cv2.contourArea)[-1]
  x,y,w,h = cv2.boundingRect(cnt)
  new_img = img[y:y+h, x:x+w]

  return new_img        

def transBg(img):   
  gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
  th, threshed = cv2.threshold(gray, 240, 255, cv2.THRESH_BINARY_INV)

  kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (11,11))
  morphed = cv2.morphologyEx(threshed, cv2.MORPH_CLOSE, kernel)

  _, roi, _ = cv2.findContours(morphed, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)

  mask = np.zeros(img.shape, img.dtype)

  cv2.fillPoly(mask, roi, (255,)*img.shape[2], )

  masked_image = cv2.bitwise_and(img, mask)

  return masked_image

def fourChannels(img):
  height, width, channels = img.shape
  if channels < 4:
    new_img = cv2.cvtColor(img, cv2.COLOR_BGR2BGRA)
    return new_img

  return img

s_img = cv2.imread(file_name, -1)

# set to 4 channels
s_img = fourChannels(s_img)

# remove white background
s_img = cut(s_img)

# set background transparent
s_img = transBg(s_img)

cv2.imwrite("/path/to/store/img.png", s_img)

输入是：

在此处输入图像描述

输出是具有透明背景的图像：

在此处输入图像描述

于 2019-02-14T21:48:59.150 回答
3

对于较新的 OpenCV 版本

import cv2
import numpy as np

file_name = "/path/to/img.png"

def cut(img):
  # crop image
  gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
  th, threshed = cv2.threshold(gray, 240, 255, cv2.THRESH_BINARY_INV)

  kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (11,11))
  morphed = cv2.morphologyEx(threshed, cv2.MORPH_CLOSE, kernel)

  cnts, _ = cv2.findContours(morphed, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
  cnt = sorted(cnts, key=cv2.contourArea)[-1]
  x,y,w,h = cv2.boundingRect(cnt)
  new_img = img[y:y+h, x:x+w]

  return new_img        

def transBg(img):   
  gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
  th, threshed = cv2.threshold(gray, 240, 255, cv2.THRESH_BINARY_INV)

  kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (11,11))
  morphed = cv2.morphologyEx(threshed, cv2.MORPH_CLOSE, kernel)

  roi, _ = cv2.findContours(morphed, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)

  mask = np.zeros(img.shape, img.dtype)

  cv2.fillPoly(mask, roi, (255,)*img.shape[2], )

  masked_image = cv2.bitwise_and(img, mask)

  return masked_image

def fourChannels(img):
  height, width, channels = img.shape
  if channels < 4:
    new_img = cv2.cvtColor(img, cv2.COLOR_BGR2BGRA)
    return new_img

  return img

s_img = cv2.imread(file_name, -1)

# set to 4 channels
s_img = fourChannels(s_img)

# remove white background
s_img = cut(s_img)

# set background transparent
s_img = transBg(s_img)

cv2.imwrite("/path/to/store/img.png", s_img)
于 2020-09-24T07:19:25.087 回答