plt.imshow()在另一個影像中顯示影像

我是 Python 新手，如果這是非常基本的，我深表歉意。我正在做影像處理，但是當我使用 cv2 讀取 png 影像然后使用 plt.imshow() 顯示影像時，它給了我奇怪的影像（帶有額外邊界的影像）。我做了以下。

import cv2
import numpy as np

img1 = cv2.imread('img.png',cv2.IMREAD_GRAYSCALE)
plt.figure(figsize=(10,4))
plt.imshow(img1, 'gray')
plt.title("ORIGINAL")
plt.savefig("original.png")

  
kernel = np.ones((4,4),np.uint8)
opening = cv2.morphologyEx(img1, cv2.MORPH_OPEN, kernel)
plt.figure(figsize=(10,4))
plt.imshow(opening, 'gray')
plt.title("OPENING OF ORIGINAL")
plt.savefig("opening of original.png")

我在此處附上生成的影像。

[原圖]

[通過 plt.imshow() 顯示影像后。]

【做開圖處理技術后】

uj5u.com熱心網友回復：

你說的額外部分是紅色區域嗎？

如果我理解正確，此代碼可用于剪切圖片的透明部分

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

def cv2_crop(im, box):
    return im.copy()[box[1]:box[3], box[0]:box[2], :]

def get_transparency_location(image):
    height, width, channel = image.shape  
    assert channel == 4  
    first_location = None  
    last_location = None  
    first_transparency = []  
    last_transparency = []  
    for y, rows in enumerate(image):
        for x, BGRA in enumerate(rows):
            alpha = BGRA[3]
            if alpha != 0:
                if not first_location or first_location[1] != y:  
                    first_location = (x, y)  
                    first_transparency.append(first_location)
                last_location = (x, y)  
        if last_location:
            last_transparency.append(last_location)

    top = first_transparency[0]
    bottom = first_transparency[-1]
    left = None
    right = None
    for first, last in zip(first_transparency, last_transparency):
        if not left:
            left = first
        if not right:
            right = last
        if first[0] < left[0]:
            left = first
        if last[0] > right[0]:
            right = last

    upper_left = (left[0], top[1])  
    bottom_right = (right[0], bottom[1])  
    box =upper_left[0], upper_left[1], bottom_right[0], bottom_right[1]
    result = cv2_crop(image, box)
    #cv2.imwrite('result.png', result)
    return result
    


if __name__ == '__main__':
    #img1 = cv2.imread('img.png',cv2.IMREAD_GRAYSCALE)
    image = cv2.imread('img.png', cv2.IMREAD_UNCHANGED)  
    img1 = get_transparency_location(image)

    plt.figure(figsize=(10,4))
    plt.imshow(img1, 'gray')
    plt.title("ORIGINAL")
    plt.savefig("original.png")


    kernel = np.ones((4,4),np.uint8)
    opening = cv2.morphologyEx(img1, cv2.MORPH_OPEN, kernel)
    plt.figure(figsize=(10,4))
    plt.imshow(opening, 'gray')
    plt.title("OPENING OF ORIGINAL")
    plt.savefig("opening of original.png")

uj5u.com熱心網友回復：

以下是如何在不添加任何框架或填充的情況下按原樣保存影像：

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

img1 = cv2.imread('matches.png', cv2.IMREAD_GRAYSCALE) 
kernel = np.ones((4, 4), np.uint8)
opening = cv2.morphologyEx(img1, cv2.MORPH_OPEN, kernel)
fig = plt.figure(frameon=False)
fig.set_size_inches(10, 4)
ax = plt.Axes(fig, [0., 0., 1., 1.])
ax.set_axis_off()
fig.add_axes(ax)

ax.imshow(img1, cmap='gray', aspect='auto')
fig.savefig("original.png")

ax.imshow(opening, cmap='gray', aspect='auto')
fig.savefig("opening of original.png")

輸入影像：

輸出影像：

當然，如果您不需要使用matplotlib，您可以簡單地使用cv2.imwrite()來撰寫影像（并cv2.show()顯示影像）：

import cv2
import numpy as np

img1 = cv2.imread('matches.png', cv2.IMREAD_GRAYSCALE) 
kernel = np.ones((4,4),np.uint8)
opening = cv2.morphologyEx(img1, cv2.MORPH_OPEN, kernel)

cv2.imwrite("original.png", img1)
cv2.imwrite("opening of original.png", opening)

標籤：Python opencv matplotlib 图像处理

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