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---
license: apache-2.0
task_categories:
- video-text-to-text
- image-to-text
language:
- en
tags:
- colab
- notebook
- demo
- vlm
- models
- hf
- ocr
- reasoning
- code
size_categories:
- n<1K
---
# **VLM-Video-Understanding**
> A minimalistic demo for image inference and video understanding using OpenCV, built on top of several popular open-source Vision-Language Models (VLMs). This repository provides Colab notebooks demonstrating how to apply these VLMs to video and image tasks using Python and Gradio.
## Overview
This project showcases lightweight inference pipelines for the following:
- Video frame extraction and preprocessing
- Image-level inference with VLMs
- Real-time or pre-recorded video understanding
- OCR-based text extraction from video frames
## Models Included
The repository supports a variety of open-source models and configurations, including:
- Aya-Vision-8B
- Florence-2-Base
- Gemma3-VL
- MiMo-VL-7B-RL
- MiMo-VL-7B-SFT
- Qwen2-VL
- Qwen2.5-VL
- Qwen-2VL-MessyOCR
- RolmOCR-Qwen2.5-VL
- olmOCR-Qwen2-VL
- typhoon-ocr-7b-Qwen2.5VL
Each model has a dedicated Colab notebook to help users understand how to use it with video inputs.
## Technologies Used
- **Python**
- **OpenCV** – for video and image processing
- **Gradio** – for interactive UI
- **Jupyter Notebooks** – for easy experimentation
- **Hugging Face Transformers** – for loading VLMs
## Folder Structure
```
├── Aya-Vision-8B/
├── Florence-2-Base/
├── Gemma3-VL/
├── MiMo-VL-7B-RL/
├── MiMo-VL-7B-SFT/
├── Qwen2-VL/
├── Qwen2.5-VL/
├── Qwen-2VL-MessyOCR/
├── RolmOCR-Qwen2.5-VL/
├── olmOCR-Qwen2-VL/
├── typhoon-ocr-7b-Qwen2.5VL/
├── LICENSE
└── README.md
````
## Getting Started
1. Clone the repository:
```bash
git clone https://github.com/PRITHIVSAKTHIUR/VLM-Video-Understanding.git
cd VLM-Video-Understanding
````
2. Open any of the Colab notebooks and follow the instructions to run image or video inference.
3. Optionally, install dependencies locally:
```bash
pip install opencv-python gradio transformers
```
## Hugging Face Dataset
The models and examples are supported by a dataset on Hugging Face:
[VLM-Video-Understanding](https://huggingface.co/datasets/prithivMLmods/VLM-Video-Understanding)
## License
This project is licensed under the Apache-2.0 License. |