ClearML Dataset: ML-Based Pathloss Radio Map Predictor

This repository contains the dataset and upload script for a machine learning pipeline that predicts radio pathloss using environmental and signal data. The project is designed for seamless tracking and reproducibility via ClearML.

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📁 Project Structure

ClearML/
├── code/               # Scripts for data processing or model training (optional extension)
├── data/               # Raw or processed pathloss-related data
├── data-upload.py      # Script to upload dataset to ClearML
└── README.md           # This documentation

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🚀 Getting Started

1. Install ClearML

pip install clearml

2. Upload Dataset to ClearML

python data-upload.py

This script uses the clearml.Dataset API to upload and version your dataset.

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💡 Use Cases

• ML-based wireless pathloss prediction

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🔗 ClearML Integration

from clearml import Dataset

dataset = Dataset.get(dataset_name="pathloss_v1", dataset_project="RadioMap/Pathloss")
local_copy = dataset.get_local_copy()

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👥 Contributors

Maintained by the CCI xG Testbed research team.
For questions, reach out via GitHub Issues.

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📜 License

For academic/research use only. Contact us for broader access or commercial usage.