maya4 0.1.2

Multi-Level SAR Processing & PyTorch DataLoader

Unveiling the layers of Synthetic Aperture Radar data from Sentinel-1 missions

Overview • Installation • Quick Start • Processing Levels • Citation

🎯 Overview

Maya4 is a production-ready Python package and dataset organization dedicated to curating and providing multi-level intermediate SAR representations from Sentinel-1 acquisitions, spanning the entire processing chain from Level 0 (raw) to Level 1 (focused imagery).

The Māyā Philosophy

The name Maya4 draws inspiration from the Māyā veil in philosophy, where reality is hidden behind successive layers—just as radar echoes undergo multiple transformations before forming a final SAR image. Each processing level reveals a different aspect of the electromagnetic interaction with Earth's surface.

Why Maya4?

• 🎚️ Multi-Level Access: Complete processing chain from raw echoes to focused imagery
• 🚀 Performance: Zarr-based storage with intelligent chunk caching and lazy loading
• 🔧 Flexibility: Access any intermediate representation for research and experimentation
• ☁️ Cloud-Native: Native Hugging Face Hub integration with 68TB+ of curated data
• 📊 ML-Ready: PyTorch-compatible dataloaders optimized for pre-training workflows
• 🌍 Geographic-Aware: Built-in support for location-based clustering and filtering

🌐 Processing Levels

Maya4 exposes the complete SAR processing chain through intermediate signal representations:

Each level represents a distinct transformation in the SAR focusing pipeline, allowing researchers to:

• Experiment with custom processing algorithms
• Pre-train deep learning models on intermediate representations
• Analyze signal characteristics at different processing stages
• Develop novel focusing techniques

📦 Pre-Training Datasets

Maya4 provides curated Pre-Training (PT) datasets in cloud-native Zarr format:

Data provided by the Copernicus Sentinel-1 mission (ESA)

✨ Features

📦 Installation

Quick Install

# Using PDM (recommended)
pdm install

# Using pip
pip install -e .

Environment-Specific Installation

pdm install -G jupyter_env

pdm install -G geospatial

pdm install -G dev

pdm install -G :all

Requirements

• Python 3.8+
• PyTorch 2.0+
• CUDA (optional, for GPU acceleration)

📖 Citation

If you use Maya4 datasets or tools in your research, please cite:

@software{maya4_2024,
  author       = {Del Prete, Roberto and Maya4 Organization},
  title        = {Maya4: Multi-Level SAR Processing and Intermediate Representations},
  year         = {2024},
  publisher    = {Hugging Face},
  howpublished = {\url{https://huggingface.co/Maya4}},
  note         = {68TB+ curated Sentinel-1 Stripmap data spanning processing levels from raw to focused imagery}
}