为什么将图像调整为50％（以像素为单位）不会将其大小降低50％的KB（PIL-枕头）？

Question

tl; dr：是否可以将KB中的图像大小操纵到所需的大小？

有4种获取图像大小的方法，例如在我的另一个问题中被马克回答，我想知道大小的任何关系是否与像素的数量有任何关系？

（7460,24300,1），（2549,6075,2），（1303,2700,3），（808,1518,4），（552,972,5）

这些是> （os_stat_size，numpy_array_size，image_factor） image_factor ==已调整图像大小的因素 如您所见，调整因子与KB中的大小不成比例。

下面给出的代码非常适合调整大小。我正在尝试操纵KBS 而不是像素的图像大小。我进行了一个实验，以将整体图像大小降低50％。这个想法是给定深度，应该是恒定的，像素应以线性方式对应于图像大小（思考元数据保持恒定），

我进行了实验，并且没有使用JPEG获得结果。因此，我认为扩展程序可能会有一些问题“>第二个答案说：

JPEG文件的深度与GIF或PNG文件的方式相同。用于创建JPEG数据的转换使解压缩的连续颜色谱。

因此，我尝试了png的同一实验，并且是相同的。以下是我对两个版本进行的实验，并在jpeg和png

helper code and Imports 之间进行注释交换：工作

from PIL import Image
import numpy as np
import requests
from io import BytesIO
from os import stat
import os
import sys

def resize(image:Image, current_size:tuple, new_width_height:float)->Image:
    '''
    Resize and return Given Image
    args:
        image: Image object
        current_size: Image size as (width, height)
        new_width_height = Reshaped image's width and height. If integer is given, it'll keep the aspect ratio as it is by shrinking the Bigger dimension (width or height) to the max of new_width_height  and then shring the smaller dimension accordingly 
    '''
    fixed_size = True if isinstance(new_width_height, int) else False
    w, h = current_size

    if fixed_size:
        if h > w:
            fixed_height = new_width_height
            height_percent = (fixed_height / float(h))
            width_size = int((float(w) * float(height_percent)))
            image = image.resize((width_size, fixed_height), Image.Resampling.LANCZOS) # # Try Image.NEAREST

        else:
            fixed_width = new_width_height
            width_percent = (fixed_width / float(w))
            height_size = int((float(h) * float(width_percent)))
            image = image.resize((fixed_width, height_size), Image.Resampling.LANCZOS) 

    else:
        w, h = int(new_width_height[0]), int(new_width_height[1])
        image = image.resize((w,h), Image.Resampling.LANCZOS)


    return image

实验：

1. 实际图像统计：

url = "https://wallpaperaccess.com/full/508751.jpg"
buffer = BytesIO(requests.get(url).content)
size_buffer = buffer.getbuffer().nbytes//1024
image = Image.open(buffer)

size_uncompressed = len(image.tobytes()) // 1024

# image.save('./wallpaper.jpeg', format = 'jpeg', quality = 'keep', subsampling = False)
# size_os = os.stat('./wallpaper.jpeg').st_size // 1024
image.save('./wallpaper.PNG', format = 'PNG', quality = 'keep', subsampling = False)
size_os = os.stat('./wallpaper.PNG').st_size // 1024
numpy_size = sys.getsizeof(np.array(image)) // 1024 # same as len(image.tobytes())

print(image.size, image.format, image.mode, str(size_buffer)+' KB (buffer.getbuffer().nbytes//1024)', str(size_os)+' KB (os.stat().st_size // 1024)', str(size_uncompressed)+' KB (len(image.tobytes()) // 1024)', str(numpy_size)+' KB (sys.getsizeof(np.array(image)) // 1024)')

2. 调整大小的图像统计：

image = resize(image, image.size, max(image.size)//2)
# image.format = "JPEG" # as it'll throw error when using quality='keep' with jpeg
image.format = "PNG" 

size_uncompressed = len(image.tobytes()) // 1024


buffer = BytesIO()
# image.save(buffer, format="JPEG", format = 'jpeg', quality = 'keep', subsampling = False)
image.save(buffer, format="PNG")
size_buffer = buffer.getbuffer().nbytes//1024

# image.save('./resized_wallpaper.jpeg', format = 'jpeg', quality = 'keep', subsampling = False)
# size_os = os.stat('./resized_wallpaper.jpeg').st_size // 1024

image.save('./resized_wallpaper.PNG', format = 'PNG')
size_os = os.stat('./resized_wallpaper.PNG').st_size // 1024

numpy_size = sys.getsizeof(np.array(image)) // 1024

print(image.size, image.format, image.mode, str(size_buffer)+' KB (buffer.getbuffer().nbytes//1024)', str(size_os)+' KB (os.stat().st_size // 1024)', str(size_uncompressed)+' KB (len(image.tobytes()) // 1024)',str(numpy_size)+' KB (sys.getsizeof(np.array(image)) // 1024)')

它们实际上都不是线性的。是正常的还是我做错了什么？