【问题标题】:Python OpenCV - overlay an image with transparencyPython OpenCV - 用透明度覆盖图像
【发布时间】:2017-05-21 09:05:44
【问题描述】:

我想要实现的是将具有透明度的图像放在另一个图像之上。像这样的:

我还没有找到任何解决方案,所以我决定逐个像素地计算结果颜色。那个对我有用,但是速度很慢。 我是 OpenCV 和 Python 的新手。

这是我的代码,我想出了:

import numpy as np
import cv2

img1 = cv2.imread("img1.png", -1)
img2 = cv2.imread("img2.png", -1) # this one has transparency
h, w, depth = img2.shape

result = np.zeros((h, w, 3), np.uint8)

for i in range(h):
    for j in range(w):
        color1 = img1[i, j]
        color2 = img2[i, j]
        alpha = color2[3] / 255.0
        new_color = [ (1 - alpha) * color1[0] + alpha * color2[0],
                      (1 - alpha) * color1[1] + alpha * color2[1],
                      (1 - alpha) * color1[2] + alpha * color2[2] ]
        result[i, j] = new_color

cv2.imshow("result", result)
cv2.waitKey(0)
cv2.destroyAllWindows()

还有其他方法吗?一些更快的方式,更快? 谢谢。

【问题讨论】:

标签: python opencv transparency rgba


【解决方案1】:

答案:

import numpy as np
import cv2

from time import time

img1 = cv2.imread("./test_image/rgb.jpg", -1)
img2 = cv2.imread("./test_image/rgba.png", -1) # this one has transparency
h, w, c = img2.shape

img1 = cv2.resize(img1, (w, h), interpolation = cv2.INTER_CUBIC)
result = np.zeros((h, w, 3), np.uint8)

#slow
st = time()
for i in range(h):
for j in range(w):
        color1 = img1[i, j]
        color2 = img2[i, j]
        alpha = color2[3] / 255.0
        new_color = [ (1 - alpha) * color1[0] + alpha * color2[0],
                      (1 - alpha) * color1[1] + alpha * color2[1],
                      (1 - alpha) * color1[2] + alpha * color2[2] ]
        result[i, j] = new_color
end = time() - st
print(end)

#fast
st = time()
alpha = img2[:, :, 3] / 255.0
result[:, :, 0] = (1. - alpha) * img1[:, :, 0] + alpha * img2[:, :, 0]
result[:, :, 1] = (1. - alpha) * img1[:, :, 1] + alpha * img2[:, :, 1]
result[:, :, 2] = (1. - alpha) * img1[:, :, 2] + alpha * img2[:, :, 2]
end = time() - st
print(end)

cv2.imshow("result", result)
cv2.waitKey(0)
cv2.destroyAllWindows()

【讨论】:

  • 请不要只用代码回答,还要添加一些解释为什么这是正确的或你的代码是做什么的
  • 谢谢,这很有帮助
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