Use Python to check whether the picture is available

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foreword

In image processing and computer vision applications, checking whether an image is available is an important pre-task before subsequent image processing. This article will introduce how to use Python and OpenCV library to perform image inspection to verify the integrity and quality of images.

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1. Filter available images

To check whether an image is available, consider checking the following:

1. Whether the image file exists:
   Check whether the image file under the specified path exists.
2. Image file format:
   Verify that the extension of the image file matches the actual image format. For example, the file name is "image.jpg", but the actual content may be an image in PNG format.
3. Image file size:
   Checks if the image file size is zero bytes or exceeds some reasonable threshold.
4. Image file integrity:
   Trying to open an image file may throw an error if the image file is corrupted or invalid.
5. Image Size:
   Check that the image is a reasonable size. For example, whether the width and height are greater than zero.
6. Image Color Channels:
   Check that the image has the expected number of color channels. Typically, a color image should have three channels (red, green, blue).
7. Image pixel value range:
   Check whether the pixel value range of the image is within a reasonable range. For 8-bit images, pixel values ​​are usually between 0 and 255.

By checking the above items, the reader can initially determine whether the image is available. Of course, the specific inspection items can be adjusted and expanded according to readers' needs and application scenarios.

Two, steps

1. Install the OpenCV library:

First, make sure your system has the OpenCV library installed. It can be installed using the pip command:

pip install opencv-python

2. Import library and define function:

Import the required libraries and define a function to perform image checking. Here is an example of code that imports the library and function definitions:

import os
import cv2

def check_image(image_path):
    # 检查图片文件是否存在
    if not os.path.exists(image_path):
        print(f"图片文件不存在：{
      
      image_path}")
        return False

    # 检查图片文件格式
    valid_extensions = ['.jpg', '.jpeg', '.png', '.bmp']
    file_extension = os.path.splitext(image_path)[1].lower()
    if file_extension not in valid_extensions:
        print(f"无效的图片文件格式：{
      
      file_extension}")
        return False

    # 检查图片文件大小
    file_size = os.path.getsize(image_path)
    if file_size == 0:
        print("图片文件大小为零")
        return False

    # 检查图片文件的完整性
    try:
        img = cv2.imread(image_path)
        if img is None:
            print("无法打开图片文件")
            return False
    except Exception as e:
        print(f"无法打开图片文件：{
      
      e}")
        return False

    # 检查图片尺寸
    height, width, _ = img.shape
    if height <= 0 or width <= 0:
        print("图片尺寸异常")
        return False

    # 检查图片的颜色通道
    num_channels = len(img.shape)
    if num_channels != 3:
        print(f"无效的颜色通道数：{
      
      num_channels}")
        return False

    # 检查图片像素值范围
    min_pixel_value = img.min()
    max_pixel_value = img.max()
    if min_pixel_value < 0 or max_pixel_value > 255:
        print("图片像素值异常")
        return False

    return True

3. Perform a picture check:

Specify the image path to be checked, and call the check_image() function to perform image checking. Here's a code sample that performs an image check:

# 指定图片路径
image_path = 'image.jpg'

# 执行图片检查
result = check_image(image_path)
if result:
    print("图片检查通过")
else:
    print("图片检查未通过")

4. Realize batch image inspection

# 批量图片检查
image_folder = 'path/to/images/folder'
image_files = os.listdir(image_folder)

for image_file in image_files:
    image_path = os.path.join(image_folder, image_file)
    result = check_image(image_path)
    if result:
        print(f"图片检查通过：{
      
      image_path}")
    else:
        print(f"图片检查未通过：{
      
      image_path}")

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Summarize

By using Python and the OpenCV library, we can easily perform image inspection to verify the integrity and quality of the image. This is very important to ensure the accuracy and usability of image data. Hope this article can be helpful to readers.