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stylefinder
babupallam/stylefinder
stylefinder is a feature extraction model from babupallam. Use it when you need embeddings to search or compare text. It is set up for clip. The card lists the license as mit.
StyleFinder is a deep learning-based image retrieval system fine-tuned on the DeepFashion In-shop Clothes dataset using CLIP. It enables users to upload an image and retrieve visually similar fashion items using both…
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Updated Jun 26, 2025
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At a glance
- Task
- Feature Extraction
- Library
- clip
- License
- mit
- Access
- Public
- Created
- Jun 26, 2025
- Updated
- Jun 26, 2025
- SHA
- c08c2bdd
Datasets
Model card
From the Hugging Face model README
👗 StyleFinder – AI-Powered Fashion Visual Search
StyleFinder is a deep learning-based image retrieval system fine-tuned on the DeepFashion In-shop Clothes dataset using CLIP. It enables users to upload an image and retrieve visually similar fashion items using both zero-shot and fine-tuned CLIP variants.
🧠 Supported Models
| Model | Stage | Description |
|---|---|---|
| ViT-B/16 | Stage 3 v4 | Best fine-tuned transformer-based model |
| RN50 | Stage 3 v3 | Best fine-tuned CNN-based model |
| ViT-B/16 | Zero-shot | Official OpenAI pretrained CLIP |
| RN50 | Zero-shot | Official OpenAI pretrained CLIP |
📊 Evaluation Results
| Metric | ViT-B/16 (v4) | RN50 (v3) |
|---|---|---|
| Rank-1 | 46.24% | 53.95% |
| mAP | 0.3481 | 0.4265 |
🖼️ Precomputed Gallery Features
Gallery embeddings are stored as .pt files for fast cosine similarity search.
| File Name | Description |
|---|---|
vitb16_stage3_v4_gallery.pt | Fine-tuned ViT-B/16 gallery |
rn50_stage3_v3_gallery.pt | Fine-tuned RN50 gallery |
vitb16_zeroshot_gallery.pt | Official CLIP ViT-B/16 gallery |
rn50_zeroshot_gallery.pt | Official CLIP RN50 gallery |
These are stored in the gallery_features/ directory and can be loaded with load_gallery_features().
⚙️ How to Use
🔹 Load a Model
from model_loader import load_model
model, preprocess = load_model(arch="vitb16", stage="stage3") # or rn50 / zeroshot
- Task
- Feature Extraction
- Library
- clip
- License
- mit
- Created
- Jun 26, 2025
- Updated
- Jun 26, 2025