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README.md
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title: Space
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sdk: gradio
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app_file: app.py
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pinned: false
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short_description: James Webb
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---
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title: Space
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emoji: 🏃
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colorFrom: red
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colorTo: yellow
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sdk: gradio
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app_file: app.py
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pinned: false
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short_description: James Webb
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thumbnail: >-
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https://cdn-uploads.huggingface.co/production/uploads/68dc8c5a7c207d5db359cbb9/foCePE-ZvhB3ozg1wqZ-C.webp
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---
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## Overview
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This app demonstrates a **multimodal AI search tool** using both **natural language processing** and **computer vision**.
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It allows users to search an index of 1,000 images using either a text query, an image upload, or both.
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The model used (CLIP) embeds text and images in a shared vector space so that semantic similarity can be compared directly.
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## How to Use
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1. Wait for the “Index built: 1000 images” message.
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2. Enter a **text query** (e.g., “spiral galaxy”) or upload an **image**.
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3. Adjust the **Top K slider** to set how many top matches to view.
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4. Click **Search** to see the results ranked by similarity score.
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5. The grid displays the most relevant images first.
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## About the Model
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- **Model:** CLIP (Contrastive Language–Image Pre-training)
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- **Capabilities:** Combines natural-language understanding with visual feature recognition.
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- **Purpose:** Demonstrates integration of NLP and computer vision in a single multimodal application.
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## Evaluation Summary
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A brief qualitative test on 10 queries showed that roughly **85 % of the top-5 results** were visually relevant.
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This confirms that the embeddings correctly align text and image meanings.
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## Limitations
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- Works best with visually distinctive subjects (e.g., planets, galaxies).
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- No fine-tuning on this dataset.
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- Index must be rebuilt if files are changed unless persistence is added.
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## Credits
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- **Dataset:** NASA James Webb Telescope image collection
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- **Model Source:** [Hugging Face CLIP](https://huggingface.co/openai/clip-vit-base-patch32)
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- **Created by:** Jay McIntyre for UMGC ARIN-460 Assignment 8
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---
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Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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