Update README.md

README.md

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-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# CLIP Segmentation
+
+CLIP Segmentation Project leverages the power of OpenAI's CLIP model combined with a segmentation decoder to perform image segmentation based on textual prompts. Provide an image and a text prompt, and get segmented masks for each prompt.
+
+
+## Features
+
+- **Textual Prompt Segmentation**: Segment images based on textual prompts.
+- **Multiple Prompts**: Support for multiple prompts separated by commas.
+- **Interactive UI**: User-friendly interface for easy image uploads and prompt inputs.
+
+
+## Usage
+
+1. Upload an image using the provided interface.
+2. Enter your text prompts separated by commas.
+3. Click on "Visualize Segments" to get the segmented masks.
+4. Hover over a class to view the individual segment.
+
+## How It Works
+
+The CLIP Segmentation Project combines the power of a pretrained CLIP model with a segmentation decoder. The CLIP model, developed by OpenAI, understands images paired with natural language. By combining this with a segmentation decoder, we can generate segmented masks for images based on textual prompts, bridging the gap between vision and language in a unique way.
+
+
+## Acknowledgements
+
+- Thanks to [OpenAI](https://openai.com/) for the CLIP model.
+- Thanks to [Image Segmentation Using Text and Image Prompts](https://github.com/timojl/clipseg).