Python ipynb存储图像的格式是什么?

Python ipynb存储图像的格式是什么?,python,image,jupyter-notebook,Python,Image,Jupyter Notebook,这里是ipynb源代码的链接。我想知道这些图像保存为什么格式。我指的是这里的长字符串: "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXcAAAD4CAYAAAAXUaZHAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjMsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+A

这里是ipynb源代码的链接。我想知道这些图像保存为什么格式。我指的是这里的长字符串:

"data": {
  "image/png": "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
不停地,不停地。我正试图找到一种方法,将这个ipynb加载到Python脚本中,并使用pillow或其他库将这些图像保存到本地机器上


任何帮助都将不胜感激。

这种编码被称为base64,可以使用标准库中的Python模块进行操作。64来自所有小写ASCII字母(26)、大写字母(26)、数字0-9(10)以及字符
+
/
。结尾的
=
字符用于填充已编码的字节,以便解码算法工作。

您可以将字符串解码到Jupyter笔记本中的base64,并显示如下内容:

%matplotlib inline

import base64
import io
from PIL import Image

s = "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"


image = base64.b64decode(s)   
img = Image.open(io.BytesIO(image))
img

当然,如果需要文件,也可以将字节保存到磁盘:

image = base64.b64decode(s)       

with open (path, 'wb') as file:
    file.write(image)

我同意,知道@MattDMo会很好。如果你认为这是一个不错的解决方案,那么你有能力解决它。如果没有收到OP的消息,我可能会将其删除。我已将其恢复为0。我会保留它,它有一些好的示例代码,我留给读者去弄清楚。