AgML
AgML is a Python library that provides access to general data sets for agricultural machine learning applications. It supports TensorFlow and PyTorch frameworks. It loads data sets by downloading them through the Hugging Face Hub and converting them into DatasetDict structures in the Hugging Face format.
AgML
65Project-AgML · Agriculture & Farm Management
Common commercial products in this category: FarmLogs, Granular, Climate FieldView
- You access agricultural data sets using the Hugging Face data uploader.
- You divide data sets into training, verification, and test sets.
- You process and model the uploaded data with transformers and datasets libraries.
- • No published release
- • NeutralGitHub Issue
Zero matrices as synthetic outputs
“In your `AgML-Synthetic.ipynb`, I ran the following lines: ``` loader = agml.data.AgMLDataLoader.helios('tomato_sample') _ = agml.viz.visualize_image_and_mask(loader[0]) ``` This shows a pair of images as below, where the right seems to be correct with a segmentation result…”
- ↑ PositiveGitHub Issue
Release iNatAg datasets on Hugging Face
“Hi @amogh7joshi 🤗 Niels here from the open-source team at Hugging Face. I discovered your work through Hugging Face's daily papers as yours got featured: The paper page lets people discuss about your paper and lets them find artifacts about it (your datasets for instance), you…”