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ArtScale

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📖 Overview

ArtScale is a custom utility software application built to automate and streamline the process of upscaling digital images. Designed specifically for digital artists and stock marketplace contributors, it prepares high-quality digital assets efficiently. Beyond standard upscaling, ArtScale functions as a compliance engine that automatically handles adaptive compression, dimension enforcement, and metadata preservation to ensure images meet the strict upload requirements of platforms like Adobe Stock, Freepik, and Shutterstock.

💻 Tech Stack

  • Frontend: React.js, Tailwind CSS
  • Desktop Runtime: Electron.js, Node.js
  • Backend Orchestration: Python
  • AI & Computer Vision: Real-ESRGAN, Real-ESRNet, NCNN (Vulkan GPU Acceleration)

✨ Main Features

  • Automated high-resolution image upscaling (Standard, Face Recovery, and Digital Art models).
  • Batch processing capabilities with real-time UI progress tracking.
  • Lightweight utility design with an intuitive drag-and-drop interface.
  • Intelligent platform compliance checking (enforces Freepik's 100MP limit and Adobe Stock's 45MB limit).
  • 100% EXIF/IPTC metadata preservation to protect contributor tags and copyright information.

📦 Dependencies

  • Node.js & npm
  • Python 3.x
  • Pillow (Python Imaging Library)
  • ExifTool (CLI binary for metadata transfer)

🛠️ How to Run Locally

# 1. Clone the repository
git clone <repository_url>
cd ArtScale

# 2. Install Node.js dependencies
npm install

# 3. Set up the Python virtual environment
python -m venv .venv

# 4. Activate the virtual environment (Windows PowerShell)
.venv\Scripts\Activate.ps1 

# 5. Install Python dependencies
pip install Pillow

# 6. Run the application (Dual-Terminal approach for development)
# Open Terminal 1 and start the React server:
npm run react-start

# Open Terminal 2 and launch the Electron window:
npx electron .

About

Desktop workflow automation engine for batch image upscaling, compression, and marketplace compliance. Tech: React, Electron, Python, Real-ESRGAN.

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