AgML is a centralized, open-source framework for agricultural machine learning that simplifies access to public datasets, benchmarks, and pretrained models tailored to agricultural tasks. It supports both PyTorch and TensorFlow backends and includes tools for loading, preprocessing, and augmenting imagery and annotations for deep learning. AgML provides out-of-the-box loaders for segmentation, classification, and detection datasets (e.g., apple flower segmentation), and features modules for synthetic data generation and standard ML pipelines. Designed for research and reproducibility, it also includes experiment tracking and reproducible benchmarks.
AgML
AgML
AgML is a centralized framework for agricultural machine learning. It provides access to public agricultural datasets for common agricultural...
Organization
Project-AgML
Deployment Model
Cloud
Agricultural Production Step
All
End User
Farmers, Developers
Used for
All
TRL
7
Community Engagement
High
Number of Forks
32
Country
Universal
Licence
Disclamer
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