opencv读入图片注意事项详解1

深度学习数据预处理中常用opencv读入图片，一般在__getitem__函数中调用。本文主要介绍opencv读取图片的一些细节以及注意事项。本文中使用的图片见第6节“opencv测试使用的图片”。

1.如何通过opencv显示图片？

通过Jupyter Notebook运行OpenCV，运行cv2.imshow()时报错。

import cv2

img = cv2.imread(img_path, cv2.IMREAD_UNCHANGED)
cv2.imshow("img", img)

报错：

---------------------------------------------------------------------------
error                                     Traceback (most recent call last)
Input In [60], in 1>()
----> 1 cv2.imshow("img", img)

error: OpenCV(4.6.0) /io/opencv/modules/highgui/src/window.cpp:1267: error: (-2:Unspecified error) The function is not implemented. Rebuild the library with Windows, GTK+ 2.x or Cocoa support. If you are on Ubuntu or Debian, install libgtk2.0-dev and pkg-config, then re-run cmake or configure script in function 'cvShowImage'

解决方法：先卸载opencv，再重新安装。（ 未解决，可直接转下述方法 ）

conda remove opencv
conda install -c menpo opencv

pip install --upgrade pip
pip install opencv-contrib-python

参考链接：https://blog.csdn.net/tudou2013goodluck/article/details/108402055

报错：内核崩溃。

Kernel Restarting
The kernel for Untitled.ipynb appears to have died. It will restart automatically.

解决方法 ：opencv读取图片，之后使用matplotlib库显示图片。

下述两个代码均可以：

%matplotlib inline
from matplotlib import pyplot as plt
import cv2

img = cv2.imread('图片路径')
img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)

plt.imshow(img)
plt.show()

import cv2

def cv2_imshow(a, **kwargs):
    a = a.clip(0, 255).astype('uint8')
    # cv2 stores colors as BGR; convert to RGB
    if a.ndim == 3:
        if a.shape[2] == 4:
            a = cv2.cvtColor(a, cv2.COLOR_BGRA2RGBA)
        else:
            a = cv2.cvtColor(a, cv2.COLOR_BGR2RGB)

    return plt.imshow(a, **kwargs)

参考链接：https://github.com/jupyter/notebook/issues/3935

2.opencv读入图片默认为BGR

img_path = "00001.png"    # 图片路径
mask_path = "00001_matte.png"  # 对应的图像分割标签路径

%matplotlib inline
from matplotlib import pyplot as plt
import cv2
import numpy as np

img_bgr = cv2.imread(img_path, cv2.IMREAD_COLOR)
img_rgb = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)  # BGR->RGB

plt.imshow(img)
plt.show()