如何在 Python 中压缩图像

2024年8月29日 | 阅读 7 分钟

本教程将教我们如何使用 Python 脚本压缩给定的图像。图像压缩是一个在不降低图像质量的情况下减小图像大小的过程。互联网上有很多工具，我们需要上传并压缩图像而不会丢失原始质量。如果我们想快速可靠地减小图像大小，它们大多数都是不错的选择。但是，我们不会使用任何第三方 API 来做到这一点。我们将在 Python 脚本中使用 Pillow 库。

让我们开始编写 Python 代码。

安装 Pillow 库

首先，我们使用 pip 命令安装 pillow 库。

安装库后，将其导入我们的文件。

import os
from PIL import Image

在我们深入研究图像压缩之前，让我们创建一个以下函数，以用户友好的格式打印文件大小。

示例 -

def get_size_format(b, factor=1024, suffix="B"):
    """
    Scale bytes to its proper byte format
    e.g:
        1253656 => '1.20MB'
        1253656678 => '1.17GB'
    """
    for unit in ["", "K", "M", "G", "T", "P", "E", "Z"]:
        if b < factor:
            return f"{b:.2f}{unit}{suffix}"
        b /= factor
    return f"{b:.2f}Y{suffix}"

现在我们将编写用于压缩图像的函数。让我们来理解下面的函数。

示例 -

def compress_given_img(image_name, new_size_ratio=0.9, quality=90, image_width=None, height_width=None, to_jpg=True):
    # loading the uploaded image to memory
    img = Image.open(image_name)
    # printing the original image shape
    print("[*] The size of image:", img.size)
    # getting the original image size in bytes
    image_size = os.path.getsize(image_name)
    # printting the size before compression/resizing
    print("[*] Size before compression:", get_size_format(image_size))
    if new_size_ratio < 1.0:
        img = img.resize((int(img.size[0] * new_size_ratio), int(img.size[1] * new_size_ratio)), Image.ANTIALIAS)
        # print new image shape
        print("New Image shape:", img.size)
    elif image_width and height_width:
        # if image_width and height_width are set, resize with them instead
        img = img.resize((image_width, height_width), Image.ANTIALIAS)
        # print new image shape
        print("New Image shape:", img.size)
    # split the filename and extension
    filename, ext = os.path.splitext(image_name)
    # make new filename appending _compressed to the original file name
    if to_jpg:
        # change the extension to JPEG
        new_filename = f"{filename}_compressed.jpg"
    else:
        # retain the same extension of the original image
        new_filename = f"{filename}_compressed{ext}"
    try:
        # save the image with the corresponding quality and optimize set to True
        img.save(new_filename, quality=quality, optimize=True)
    except OSError:
        # convert the image to RGB mode first
        img = img.convert("RGB")
        # save the image with the corresponding quality and optimize set to True
        img.save(new_filename, quality=quality, optimize=True)
    print(" New file saved:", new_filename)
    # get the new image size in bytes
    new_image_size = os.path.getsize(new_filename)
    # print the new size in a good format
    print("Size after compression:", get_size_format(new_image_size))
    # calculate the saving bytes
    saving_diff = new_image_size - image_size
    # print the saving percentage
    print(f" Image size change: {saving_diff/image_size*100:.2f}% of the original image size.")

让我们分解上面的函数并理解它是如何工作的。

在上面的代码中，我们创建了一个名为 compress_given_image() 的函数，该函数接受多个参数 -

首先，我们使用 image.open() 函数将图像加载到内存中。我们使用 os.path.getsize() 获取图像大小，以便稍后可以将此大小与新生成的文件大小进行比较。
我们使用条件语句，如果 new_size_ratio 低于 1.0，则必须执行重 sizing。这个数字的范围是 0 到 1，并乘以原始图像的宽度和高度，从而生成一个较低分辨率的图像。如果您想进一步减小图像大小，此参数非常合适。您也可以将其设置为 0.95 或 0.9，以在分辨率变化最小的情况下减小图像大小。
如果 new_size_ratio 为 1，但 height 和 width 已设置，我们则将图像调整为新的 width 和 height 值。但我们需要确保它们应低于原始 width 和 height。
在以下条件中，我们检查 to_jpg 是否为 True，然后将原始图像的扩展名更改为 JPEG。这将大大减小图像大小，尤其是对于 PNG 图像。如果我们遇到 OSError，可以通过将图像格式转换为 RGB 来解决此问题。
最后，我们使用 save() 方法写入优化后的图像，我们将 optimize 设置为 True，并将 quality 参数从函数传递过去。然后我们获取压缩图像的大小并将其与原始图像的大小进行比较。

现在我们在主函数中调用上面的函数，并将使用 argparse 模块将其与命令行参数集成。让我们来理解下面的代码。

if __name__ == "__main__":
    import argparse
    parser = argparse.ArgumentParser(description="Python script for compressing and resizing images")
    parser.add_argument("image", help="Given image to compress and/or resize")
    parser.add_argument("-j", "--to-jpg", action="store_true", help="Whether to convert the image to the JPEG format")
    parser.add_argument("-q", "--quality", type=int, help="Quality ranging from a minimum of 0 (worst) to a maximum of 95 (best). Default is 90", default=90)
    parser.add_argument("-r", "--resize-ratio", type=float, help="We are resizing ratio from 0 to 1, setting to 0.5 will multiply width & height of the image by 0.5. Default is 1.0", default=1.0)
    parser.add_argument("-w", "--width", type=int, help="The new width image, make sure to set it with the `height` parameter")
    parser.add_argument("-hh", "--height", type=int, help="The new height for the image, make sure to set it with the `width` parameter")
    args = parser.parse_args()
    # print the passed arguments
    print("="*50)
    print("Image:", args.image)
    print("To JPEG:", args.to_jpg)
    print("Quality:", args.quality)
    print("Resizing ratio:", args.resize_ratio)
    if args.width and args.height:
        print("Width:", args.width)
        print("Height:", args.height)
    print("="*50)
    # compress the image
    compress_given_img(args.image, args.resize_ratio, args.quality, args.width, args.height, args.to_jpg)

在上面的代码中，我们创建了命令行参数解析器，并添加了我们之前讨论过的参数。让我们在命令行中运行我们的脚本。

完整脚本

import os
from PIL import Image

# Get the Image Size
def get_size_format(b, factor=1024, suffix="B"):
    """
    Scale bytes to its proper byte format
    e.g:
        1253656 => '1.20MB'
        1253656678 => '1.17GB'
    """
    for unit in ["", "K", "M", "G", "T", "P", "E", "Z"]:
        if b < factor:
            return f"{b:.2f}{unit}{suffix}"
        b /= factor
    return f"{b:.2f}Y{suffix}"

# To compress the given image
def compress_given_img(image_name, new_size_ratio=0.9, quality=90, image_width=None, height_width=None, to_jpg=True):
    # loading the uploaded image to memory
    img = Image.open(image_name)
    # printing the original image shape
    print("[*] The size of image:", img.size)
    # getting the original image size in bytes
    image_size = os.path.getsize(image_name)
    # printting the size before compression/resizing
    print("[*] Size before compression:", get_size_format(image_size))
    if new_size_ratio < 1.0:
        img = img.resize((int(img.size[0] * new_size_ratio), int(img.size[1] * new_size_ratio)), Image.ANTIALIAS)
        # print new image shape
        print("New Image shape:", img.size)
    elif image_width and height_width:
        # if image_width and height_width are set, resize with them instead
        img = img.resize((image_width, height_width), Image.ANTIALIAS)
        # print new image shape
        print("New Image shape:", img.size)
    # split the filename and extension
    filename, ext = os.path.splitext(image_name)
    # make new filename appending _compressed to the original file name
    if to_jpg:
        # change the extension to JPEG
        new_filename = f"{filename}_compressed.jpg"
    else:
        # retain the same extension of the original image
        new_filename = f"{filename}_compressed{ext}"
    try:
        # save the image with the corresponding quality and optimize set to True
        img.save(new_filename, quality=quality, optimize=True)
    except OSError:
        # convert the image to RGB mode first
        img = img.convert("RGB")
        # save the image with the corresponding quality and optimize set to True
        img.save(new_filename, quality=quality, optimize=True)
    print(" New file saved:", new_filename)
    # get the new image size in bytes
    new_image_size = os.path.getsize(new_filename)
    # print the new size in a good format
    print("Size after compression:", get_size_format(new_image_size))
    # calculate the saving bytes
    saving_diff = new_image_size - image_size
    # print the saving percentage
    print(f" Image size change: {saving_diff/image_size*100:.2f}% of the original image size.")

if __name__ == "__main__":
    import argparse
    parser = argparse.ArgumentParser(description="Python script for compressing and resizing images")
    parser.add_argument("image", help="Given image to compress and/or resize")
    parser.add_argument("-j", "--to-jpg", action="store_true", help="Whether to convert the image to the JPEG format")
    parser.add_argument("-q", "--quality", type=int, help="Quality ranging from a minimum of 0 (worst) to a maximum of 95 (best). Default is 90", default=90)
    parser.add_argument("-r", "--resize-ratio", type=float, help="We are resizing ratio from 0 to 1, setting to 0.5 will multiply width & height of the image by 0.5. Default is 1.0", default=1.0)
    parser.add_argument("-w", "--width", type=int, help="The new width image, make sure to set it with the `height` parameter")
    parser.add_argument("-hh", "--height", type=int, help="The new height for the image, make sure to set it with the `width` parameter")
    args = parser.parse_args()
    # print the passed arguments
    print("="*50)
    print("Image:", args.image)
    print("To JPEG:", args.to_jpg)
    print("Quality:", args.quality)
    print("Resizing ratio:", args.resize_ratio)
    if args.width and args.height:
        print("Width:", args.width)
        print("Height:", args.height)
    print("="*50)
    # compress the image
    compress_given_img(args.image, args.resize_ratio, args.quality, args.width, args.height, args.to_jpg)

现在在命令行终端中运行上面的脚本。

$ python main.py house.jpg

输出

==================================================
Image: house.jpg
To JPEG: False
Quality: 90
Resizing ratio: 1.0
==================================================
[*] The size of image: (275, 183)
[*] Size before compression: 180.94KB
 New file saved: house_compressed.jpg
Size after compression: 100.21KB
 Image size change: 47.81% of the original image size.

$ python main.py nature.jpg -j

输出

==================================================
Image: nature.jpg
To JPEG: True
Quality: 90
Resizing ratio: 1.0
==================================================
[*] The size of image: (612, 384)
[*] Size before compression: 80.67KB
 New file saved: nature_compressed.jpg
Size after compression: 73.37KB
 Image size change: 4.45% of the original image size.

$ python main.py sample_image.png -j -q 75

输出

==================================================
Image: sample_image.png
To JPEG: True
Quality: 75
Resizing ratio: 1.0
==================================================
[*] The size of image: (740, 935)
[*] Size before compression: 146.32KB
 New file saved: sample_image_compressed.jpg
Size after compression: 123.03KB
 Image size change: -15.92% of the original image size.

$ python main.py sample_image.png -j -q 75 -w 800 -hh 400

==================================================
Image: sample_image.png
To JPEG: True
Quality: 75
Resizing ratio: 1.0
Width: 800
Height: 400
==================================================
[*] The size of image: (740, 935)
[*] Size before compression: 146.32KB
main.py:34: DeprecationWarning: ANTIALIAS is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.LANCZOS instead.
  img = img.resize((image_width, height_width), Image.ANTIALIAS)
New Image shape: (800, 400)
 New file saved: sample_image_compressed.jpg
Size after compression: 61.76KB
 Image size change: -57.79% of the original image size.

结论

在本教程中，我们解释了如何通过 Python 脚本在恢复原始质量的同时减小图像。我们可以不使用任何第三方工具来压缩图像。您可以复制代码并在您的系统上运行。

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