https://github.com/dwqs/ollama-ocr

A powerful OCR (Optical Character Recognition) package that uses state-of-the-art vision language models
https://github.com/dwqs/ollama-ocr

Last synced: 8 months ago
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A powerful OCR (Optical Character Recognition) package that uses state-of-the-art vision language models

• Host: GitHub
• URL: https://github.com/dwqs/ollama-ocr
• Owner: dwqs
• License: mit
• Created: 2025-01-01T14:04:45.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2025-01-01T14:59:43.000Z (over 1 year ago)
• Last Synced: 2025-01-01T15:29:27.828Z (over 1 year ago)
• Language: Vue
• Size: 64.5 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
> inspired by [imanoop7/Ollama-OCR](https://github.com/imanoop7/Ollama-OCR)

## Ollama OCR for web

A powerful OCR (Optical Character Recognition) package that uses state-of-the-art vision language models through Ollama to extract text from images.

## Supported Models

- **LLaVA**: A multimodal model that combines a vision encoder and Vicuna for general-purpose visual and language understanding, achieving impressive chat capabilities mimicking spirits of the multimodal GPT-4. (LLaVa model can generate wrong output sometimes)

- **Llama 3.2 Vision**: Instruction-tuned models are optimized for visual recognition, image reasoning, captioning, and answering general questions about an image

- **MiniCPM-V 2.6**: A GPT-4V Level MLLM for Single Image, Multi Image and Video on Your Phone

## Quick Start

#### Prerequisites

1. Install [Ollama](https://ollama.com/)

2. Pull the required models:

```sh

ollama pull llama3.2-vision:11b

ollama pull llava:13b

ollama pull minicpm-v:8b

```

Then run following command:

```sh

git clone git@github.com:dwqs/ollama-ocr.git

cd ollama-ocr

yarn or npm i

yarn dev or npm run dev

```

## Docker Supports

**you can run the demo from docker**: `debounce/ollama-ocr`

## Examples

#### Input Image1

![input-image](https://image-static.segmentfault.com/149/814/1498143911-677575ecd6977_fix732)

#### Output Markdown

![output-markdown.png](https://image-static.segmentfault.com/338/339/3383395719-67757691e9b37_fix732)

#### Input Image2

![input-image](https://image-static.segmentfault.com/257/222/2572220334-677579c2747c7_fix732)

#### Output JSON

![output-json.png](https://image-static.segmentfault.com/104/188/1041885248-677579f517f02_fix732)

## Output Format Details

- **Markdown Format**: The output is a markdown string containing the extracted text from the image.

- **Text Format**: The output is a plain text string containing the extracted text from the image.

- **JSON Format**: The output is a JSON object containing the extracted text from the image.

## License

MIT