TerraTorch让遥感模型微调像搭积木一样简单，一键完成训练与评测。
TerraTorch: The Geospatial Foundation Models Toolkit
- 模块化设计，支持卫星/气象/气候数据的快速微调
- 配置文件驱动，无需编码即可运行训练任务
- 集成GEO-Bench，支持可复现的遥感模型评测
TerraTorch 是一个基于 PyTorch Lightning 构建的遥感基础模型微调与评测工具包，专为卫星、气象和气候数据设计。它整合了领域特定的数据模块、预定义任务及模块化模型工厂，可将任意骨干网络与多种解码器头灵活搭配。研究人员只需修改训练配置文件即可实现零代码微调。通过集成自动化超参数优化工具 Iterate 和 GEO-Bench，该工具包显著降低模型开发所需的专业知识与时间成本。TerraTorch 已开源，采用 Apache 2.0 许可证，可通过 pip install terratorch 安装使用。
原文摘要 · Abstract (English)
TerraTorch is a fine-tuning and benchmarking toolkit for Geospatial Foundation Models built on PyTorch Lightning and tailored for satellite, weather, and climate data. It integrates domain-specific data modules, pre-defined tasks, and a modular model factory that pairs any backbone with diverse decoder heads. These components allow researchers and practitioners to fine-tune supported models in a no-code fashion by simply editing a training configuration. By consolidating best practices for model development and incorporating the automated hyperparameter optimization extension Iterate, TerraTorch reduces the expertise and time required to fine-tune or benchmark models on new Earth Observation use cases. Furthermore, TerraTorch directly integrates with GEO-Bench, allowing for systematic and reproducible benchmarking of Geospatial Foundation Models. TerraTorch is open sourced under Apache 2.0, available at https://github.com/IBM/terratorch, and can be installed via pip install terratorch.
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