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title: Jewelry Recommender
emoji: 💎
colorFrom: purple
colorTo: pink
sdk: gradio
sdk_version: 3.50.2
app_file: updatedcode/app.py
pinned: false
license: mit
duplicated_from: null
models:
- efficientnet
- faiss
python_version: 3.9
datasets:
- None
tags:
- image-similarity
- jewelry
- recommendation-system
- computer-vision
# Gradio configuration
gradio:
theme: default
dark_background: False
live: False
capture_session: False
allow_flagging: never
queue_concurrency_count: 1
max_file_size: 10
# System dependencies
dependencies:
-torch>=2.0.0
-torchvision>=0.15.0
-faiss-cpu>=1.7.0
-scikit-learn>=1.0.0
-numpy>=1.20.0
-pandas>=1.3.0
-pyarrow>=7.0.0
-matplotlib>=3.5.0
-Pillow>=9.0.0
-tqdm>=4.60.0
-ipywidgets>=7.7.0
-gdown>=4.5.0
-gradio>=3.0.0
-concurrent-log-handler>=0.9.20
-plotly>=5.10.0
# Space hardware
hardware:
accelerator: cpu
cpu: 2
memory: 16GB
# Required files for the application
files:
- app.py
- jewelry_index.idx
- jewelry_metadata.pkl
- README.md
# Documentation
information:
description: >
This Jewelry Recommender app uses computer vision to find similar jewelry items
based on a reference image. Upload an image of jewelry, provide an image URL,
or paste a base64-encoded image to get visually similar recommendations.
The system uses an EfficientNet model for feature extraction and FAISS for fast similarity search.
license: MIT
author: Maazuddin
repository: https://github.com/Maazuddin1/jewelry-recommender |