> ## Documentation Index
> Fetch the complete documentation index at: https://docs.unstructured.io/llms.txt
> Use this file to discover all available pages before exploring further.

# Extract images and tables from documents

## Task

You want to get, decode, and show elements, such as images and tables, that are embedded in a PDF document.

## Approach

Extract the Base64-encoded representation of specific elements, such as images and tables, in the document.
For each of these extracted elements, decode the Base64-encoded representation of the element into its original visual representation
and then show it.

## To run this example

You will need a document that is one of the document types supported by the `extract_image_block_types` argument.
See the `extract_image_block_types` entry in [API Parameters](/api-reference/legacy-api/partition/api-parameters).
This example uses a PDF file with embedded images and tables.

## Code

For the [Unstructured Ingest Python library](/open-source/ingestion/python-ingest), you can use the standard Python
[json.load](https://docs.python.org/3/library/json.html#json.load) function to load into a Python dictionary the contents of a JSON
file that the Ingest Python library outputs after the processing is complete.

```python Python theme={null}
import json, base64, io
from PIL import Image

def get_image_block_types(input_json_file_path: str):
    with open(input_json_file_path, 'r') as file:
        file_elements = json.load(file)

    for element in file_elements:
        if "image_base64" in element["metadata"]:
            # Decode the Base64-encoded representation of the 
            # processed "Image" or "Table" element into its original
            # visual representation, and then show it.
            image_data = base64.b64decode(element["metadata"]["image_base64"])
            image = Image.open(io.BytesIO(image_data))
            image.show()

if __name__ == "__main__":
    # Source: https://github.com/Unstructured-IO/unstructured-ingest/blob/main/example-docs/pdf/embedded-images-tables.pdf

    # Specify where to get the local file, relative to this .py file.
    get_image_block_types(
        input_json_file_path="local-ingest-output/embedded-images-tables.json"
    )
```