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