> ## Documentation Index
> Fetch the complete documentation index at: https://unstructured-53-docs-243-plugins.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Image descriptions

After partitioning and chunking, you can have Unstructured generate text-based summaries of detected images.

This summarization is done by using models offered through these providers:

* [GPT-4o](https://openai.com/index/hello-gpt-4o/), provided through OpenAI.
* [Claude 3.5 Sonnet](https://www.anthropic.com/news/claude-3-5-sonnet), provided through Anthropic.
* [Claude 3.5 Sonnet](https://aws.amazon.com/bedrock/claude/), provided through Amazon Bedrock.
* [Gemini 2.0 Flash](https://cloud.google.com/vertex-ai/generative-ai/docs/gemini-v2), provided through Vertex AI.

Here is an example of the output of a detected image using GPT-4o. Note specifically the `text` field that is added.
Line breaks have been inserted here for readability. The output will not contain these line breaks.

```json theme={null}
{
    "type": "Image",
    "element_id": "3303aa13098f5a26b9845bd18ee8c881",
    "text": "{\n  \"type\": \"graph\",\n  \"description\": \"The graph shows 
        the relationship between Potential (V) and Current Density (A/cm2). 
        The x-axis is labeled 'Current Density (A/cm2)' and ranges from 
        0.0000001 to 0.1. The y-axis is labeled 'Potential (V)' and ranges 
        from -2.5 to 1.5. There are six different data series represented 
        by different colors: blue (10g), red (4g), green (6g), purple (2g), 
        orange (Control), and light blue (8g). The data points for each series 
        show how the potential changes with varying current density.\"\n}",
    "metadata": {
        "filetype": "application/pdf",
        "languages": [
            "eng"
        ],
        "page_number": 1,
        "image_base64": "/9j...<full results omitted for brevity>...Q==",
        "image_mime_type": "image/jpeg",
        "filename": "7f239e1d4ef3556cc867a4bd321bbc41.pdf",
        "data_source": {}
    }
}
```

Any embeddings that are produced after these summaries are generated will be based on the `text` field's contents.

## Generate image descriptions

To generate image descriptions, in an **Enrichment** node in a workflow, specify the following:

<Note>
  You can change a workflow's image description settings only through [Custom](/ui/workflows#create-a-custom-workflow) workflow settings.

  Image summaries are generated only when the **Partitioner** node in a workflow is also set to use the **High Res** partitioning strategy. [Learn more](/ui/partitioning).
</Note>

Select **Image**, and then choose one of the following provider (and model) combinations to use:

* **OpenAI (GPT-4o)**. [Learn more](https://openai.com/index/hello-gpt-4o/).
* **Anthropic (Claude 3.5 Sonnet)**. [Learn more](https://www.anthropic.com/news/claude-3-5-sonnet).
* **Amazon Bedrock (Claude 3.5 Sonnet)**. [Learn more](https://aws.amazon.com/bedrock/claude/).
* **Vertex AI (Gemini 2.0 Flash)**. [Learn more](https://cloud.google.com/vertex-ai/generative-ai/docs/gemini-v2).