将图像粘贴到另一张图像上时，如何保持前景图像透明？

Question

我正在尝试使用 OpenCV / Pillow 将图像放在另一个图像之上，同时保持前景图像透明。如果你看this image，你可以看到一切都很顺利，除了我不知道如何保持图像透明。

我尝试在我的程序中实现this StackOverflow solution by @fireant，但似乎没有任何效果。

如何正常执行index.py，但保持前景png透明？

图片

dot_transparent.png

image.jpg

index.py

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import os
import numpy
import cv2
from PIL import Image
from os.path import join, dirname, realpath
import json

def upload_files():
    #https://github.com/Itseez/opencv/blob/master/data/haarcascades/haarcascade_frontalface_default.xml
    face_cascade = cv2.CascadeClassifier('/Users/matt/Python/LazerEyes/haarcascade_eye.xml')

    #https://github.com/Itseez/opencv/blob/master/data/haarcascades/haarcascade_eye.xml
    eye_cascade = cv2.CascadeClassifier('/Users/matt/Python/LazerEyes/haarcascade_eye.xml')

    img = cv2.imread('new.png')
    img_to_place = cv2.imread('dot_transparent.png')

    gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
    gray_to_place = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
    
    img_h, img_w = gray.shape
    img_to_place_h, img_to_place_w = gray_to_place.shape

    faces = face_cascade.detectMultiScale(gray, 1.3, 5)
    for (x,y,w,h) in faces:
        roi_gray = gray[y:y+h, x:x+w]
        roi_color = img[y:y+h, x:x+w]
        eyes = eye_cascade.detectMultiScale(roi_gray)
        for (ex,ey,ew,eh) in eyes:
            resized_img = cv2.resize(img_to_place, (eh, ew), interpolation = cv2.INTER_AREA)
            resized_img_h, resized_img_w, _ = resized_img.shape

            roi_color[ey:ey+resized_img_h, ex:ex+resized_img_w, :] = resized_img

Answer 1

由于每个像素都有特定的 alpha 值，我将采用另一种方法，并实现像素级alpha blending，忽略最终图像中的任何 alpha 通道。

借用Quang Hoang's answer的一些台词：

import cv2
import matplotlib.pyplot as plt
import numpy as np

# Read images
img = cv2.imread('image.jpg')
dot = cv2.imread('dot_transparent.png', cv2.IMREAD_UNCHANGED)

# Manual manipulating one eye
ex, ey, ew, eh = 1430, 1490, 400, 400
dot = cv2.resize(dot, (eh, ew))

# Prepare pixel-wise alpha blending
dot_alpha = dot[..., 3] / 255.0
dot_alpha = np.repeat(dot_alpha[..., np.newaxis], 3, axis=2)
dot = dot[..., :3]

# Pixel-wise alpha blending
img[ey:ey+eh, ex:ex+ew, :] = img[ey:ey+eh, ex:ex+ew, :] * (1 - dot_alpha) + dot * dot_alpha

# Output
plt.figure(figsize=(9, 9))
plt.imshow(img[..., [2, 1, 0]])
plt.tight_layout()
plt.show()

这就是输出：

----------------------------------------
System information
----------------------------------------
Platform:      Windows-10-10.0.16299-SP0
Python:        3.9.1
Matplotlib:    3.3.4
NumPy:         1.20.1
OpenCV:        4.5.1
----------------------------------------

Answer 2

用cv2.IMREAD_UNCHANGE 标志读取dot_transparent.png，然后你就有了alpha通道（否则你只有3个通道）

img = cv2.imread('faces.jpg')
to_replace = cv2.imread('dot_transparent.png', cv2.IMREAD_UNCHANGED)
# sample eye dectection
ex,ey,ew,eh = 1600, 1600,200,200

resized_replace = cv2.resize(to_replace, (eh,ew))

img[ey:ey+eh, ex:ex+ew] = np.where(resized_replace[...,-1:]<50, 
                                   img[ey:ey+eh, ex:ex+ew],
                                   resized_replace[...,:-1]
                            )

# show with imshow
plt.imshow(img[...,::-1])

输出：