CatchTheTornado / ai-product-descriptor

This is an PoC of a REST service extracting product text description and structuralized attributes from product image.

AI Product Descriptor

This is an PoC of a REST service extracting product text description and structuralized attributes from product image.

Potential use cases:

• automate product description for eCommerce and PIM's,
• visual search engines,
• ...

Example usage

Input:

Output:

{
    "description": "Unleash your style with these **iconic sports-inspired sneakers**. Crafted for comfort and designed for an active lifestyle, these sneakers feature a sleek, **low-top silhouette** with a durable **white and silver mesh upper with synthetic overlays** for breathability and support. Accented by **signature swoosh logos** in a contrasting black, this pair adds an edgy pop to your outfits. Secure your fit with **black laces** atop a classic lace-up closure. A padded **red collar** provides extra ankle support, while the soft fabric lining ensures a comfortable in-shoe feel. Built to last, the **rubber outsole with a traction pattern** enhances grip, and a visible **air cushioning unit** in the heel absorbs impact. These sneakers are a perfect blend of style, performance, and comfort, making them suitable for both athletic activities and casual wear.",
    "attributes": [
        {
            "category": "Footwear"
        },
        {
            "style": "Sports Sneaker"
        },
        {
            "color": "White/Silver with Red and Black accents"
        },
        {
            "closure_type": "Lace-up"
        },
        {
            "material_upper": "Mesh with Synthetic Overlays"
        },
        {
            "logo": "Swoosh"
        },
        {
            "collar_type": "Padded"
        },
        {
            "lining_material": "Fabric"
        },
        {
            "sole_material": "Rubber"
        },
        {
            "cushioning": "Visible Air Unit"
        },
        {
            "pattern": "Traction"
        },
        {
            "gender": "Unisex"
        },
        {
            "size": "Not specified"
        },
        {
            "condition": "New"
        }
    ]
}

Getting Started

This guide will walk you through the process of checking out and setting up the project on your local machine for development and testing purposes.

Prerequisites

Before you begin, ensure you have the following installed on your system:

• Python 3.6+
• Git

Installation

1. Clone the Repository

   First, clone the repository to your local machine using Git:

   git clone https://github.com/yourusername/your_project_name.git
   cd your_project_name
   

2. Create a Virtual Environment (Optional but Recommended)

   It's a good practice to create a virtual environment for your Python projects. Use the following commands to create and activate one:

   • For Unix or MacOS:

     python3 -m venv env
     source env/bin/activate

   • For Windows:

     python -m venv env
     .\env\Scripts\activate

3. Install Dependencies

   Install the required packages using:

   pip install -r requirements.txt

4. Running the Application

   To run the application please do use

   export OPENAI_API_KEY={your API key from platform.chatgpt.com}
   uvicorn app.main:app --reload
   

   Now, you're ready to query the service:

    curl -X POST http://localhost:8000/describe/ \
         -H "Content-Type: application/json" \
         -d '{"image_url": "https://upload.wikimedia.org/wikipedia/commons/4/49/Sports_shoes.jpg"}'

TODO

1. Add async call support.
2. Authorization support
3. ...