使用cv2进行图像融合

冷不防 2022-11-16 01:37 247阅读 0赞

加入我们有两张图，分别是这样：

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3pob3VfNDM4_size_16_color_FFFFFF_t_70][]

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3pob3VfNDM4_size_16_color_FFFFFF_t_70 1][]

我们想要将第二个放置在第一个图上，直接贴图就是这样的：

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3pob3VfNDM4_size_16_color_FFFFFF_t_70 2][]

这样贴着，没啥意义，我们使用seamlessClone处理一下就会变得很好：

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3pob3VfNDM4_size_16_color_FFFFFF_t_70 3][]

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3pob3VfNDM4_size_16_color_FFFFFF_t_70 4][]

看着自然很多了吧，上述的代码如下：

import cv2
    import numpy as np
    
    b3=cv2.imread('b3.jpg')
    b2=cv2.imread('b2.jpg')
    #b1=cv2.resize(b1,(256,256))
    center_x=300
    center_y=500
    
    #normal_clone
    mask = 255 * np.ones(b3.shape, b3.dtype)
    normal_clone = cv2.seamlessClone(b3, b2, mask, (center_x+256,center_y-256), cv2.NORMAL_CLONE)
    cv2.imshow('normal_clone',normal_clone)
    #max_clone
    max_clone = cv2.seamlessClone(b3, b2, mask, (center_x+256,center_y-256), cv2.MIXED_CLONE)
    cv2.imshow('max_clone',max_clone)
    #直接贴
    #print(b3.shape)
    b2[200:416,300:1151]=b3
    cv2.imshow('b2',b2)
    cv2.waitKey(0)

同样，我们想讲一个美女头像贴在这个草原上：

先看一下直接贴的效果：

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3pob3VfNDM4_size_16_color_FFFFFF_t_70 5][]

看着是不是很别扭

接下使用seamlessClone看一下：

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3pob3VfNDM4_size_16_color_FFFFFF_t_70 6][]

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3pob3VfNDM4_size_16_color_FFFFFF_t_70 7][]

看着这样更自然很多，上面使用了normal\_clone和max\_clone两种模式，上述的例子看起来差别不大，但是有的例子差距就会很多，需要自己选择。

至此，使用cv2里面seamlessClone方式，应该熟悉了，代码如下：

import cv2
    import numpy as np
    
    b1=cv2.imread('b1.jpg')
    b2=cv2.imread('b2.jpg')
    b1=cv2.resize(b1,(256,256))
    center_x=300
    center_y=500
    
    #normal_clone
    mask = 255 * np.ones(b1.shape, b1.dtype)
    normal_clone = cv2.seamlessClone(b1, b2, mask, (center_x+256,center_y-256), cv2.NORMAL_CLONE)
    cv2.imshow('normal_clone',normal_clone)
    #max_clone
    max_clone = cv2.seamlessClone(b1, b2, mask, (center_x+256,center_y-256), cv2.MIXED_CLONE)
    cv2.imshow('max_clone',max_clone)
    #直接贴
    b2[center_x-128:center_x+128,center_y-128:center_y+128]=b1
    cv2.imshow('b2',b2)
    cv2.waitKey(0)

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