Update README.md

README.md

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----
-license: apache-2.0
----
+---
+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.