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title: README
emoji: 🧥
colorFrom: indigo
colorTo: green
sdk: static
pinned: false
license: mit
short_description: Open-source fashion intelligence and visual search.
---
<section>
<h1>HopitAI</h1>
<p>
HopitAI builds open-source fashion intelligence models for visual search,
product matching, catalog retrieval, and ecommerce discovery.
</p>
</section>
<section>
<h2>MODA Fashion Retrieval</h2>
<p>
MODA is a family of fashion retrieval models covering both halves of the
problem: finding products from an image, and finding products from a text
description. Every model and result is MIT licensed and reproducible from
the public repository.
</p>
<p>
<a href="https://huggingface.co/spaces/HopitAI/moda-fashion-search">Try the interactive demo</a>
·
<a href="https://github.com/hopit-ai/Moda">View the GitHub repo</a>
·
<a href="https://huggingface.co/HopitAI/moda-fashion-deepfashion2">Start with DeepFashion2</a>
</p>
</section>
<section>
<h2>Featured Models</h2>
<table>
<tr>
<th>Model</th>
<th>Task</th>
<th>Best for</th>
</tr>
<tr>
<td><a href="https://huggingface.co/HopitAI/moda-fashionsiglip-multiview-203m">MODA-FashionSigLIP-MultiView-203M</a></td>
<td>Text to image</td>
<td>Searching a catalog in plain language. Multi-view retrieval system over the frozen FashionSigLIP checkpoint, adding zero parameters.</td>
</tr>
<tr>
<td><a href="https://huggingface.co/HopitAI/moda-fashion-distilled">MODA-Fashion-Distilled</a></td>
<td>Image to image</td>
<td>Best overall quality</td>
</tr>
<tr>
<td><a href="https://huggingface.co/HopitAI/moda-fashion-distilled-512d">MODA-Fashion-Distilled-512d</a></td>
<td>Image to image</td>
<td>Compact vector search indexes</td>
</tr>
<tr>
<td><a href="https://huggingface.co/HopitAI/moda-fashion-deepfashion2">MODA-Fashion-DeepFashion2</a></td>
<td>Image to image</td>
<td>Simple reproducible recipe</td>
</tr>
<tr>
<td><a href="https://huggingface.co/HopitAI/moda-fashion-vision-fp16">MODA-Fashion-Vision-FP16</a></td>
<td>Image to image</td>
<td>Smaller edge and mobile deployment</td>
</tr>
<tr>
<td><a href="https://huggingface.co/HopitAI/moda-fashion-matryoshka">MODA-Fashion-Matryoshka</a></td>
<td>Image to image</td>
<td>Flexible embedding dimensions</td>
</tr>
</table>
</section>
<section>
<h2>Quick Start</h2>
Image to image, for finding visually similar products:
```bash
huggingface-cli download HopitAI/moda-fashion-deepfashion2 --local-dir ./moda-fashion-deepfashion2
```
```python
import open_clip
model, preprocess_train, preprocess_val = open_clip.create_model_and_transforms(
"hf-hub:HopitAI/moda-fashion-deepfashion2"
)
```
Text to image, for searching a catalog in plain language:
```bash
pip install "git+https://huggingface.co/HopitAI/moda-fashionsiglip-multiview-203m"
```
```python
from moda_fashionsiglip_multiview import ModaFashionSigLIP
retriever = ModaFashionSigLIP.from_pretrained()
index = retriever.build_index(image_paths, item_ids=item_ids)
results = retriever.search("red floral summer dress", index, top_k=5)[0]
```
</section>
<section>
<h2>Use Cases</h2>
<ul>
<li>Search a fashion catalog with a natural-language query.</li>
<li>Find visually similar products in a fashion catalog.</li>
<li>Match street-style looks to shoppable items.</li>
<li>Deduplicate product images across marketplaces.</li>
<li>Build embedding indexes for ecommerce search and recommendations.</li>
</ul>
</section>
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