This is a relatively major release that introduces a significant number of new datasets into AgML, alongside various bugfixes and improvements.
New Datasets
The following new datasets have been introduced: embrapa_wgisd_grape_detection, growliflower_cauliflower_segmentation, strawberry_detection_2023, strawberry_detection_2022, almond_harvest_2021, almond_bloom_2023, gemini_flower_detection_2022, gemini_leaf_detection_2022, gemini_pod_detection_2022, gemini_plant_detection_2022, paddy_disease_classification, onion_leaf_classification, chilli_leaf_classification, orange_leaf_disease_classification, papaya_leaf_disease_classification, blackgram_plant_leaf_disease_classification, arabica_coffee_leaf_disease_classification, banana_leaf_disease_classification, coconut_tree_disease_classification, rice_leaf_disease_classification, tea_leaf_disease_classification, betel_leaf_disease_classification, java_plum_leaf_disease_classification, sunflower_disease_classification, and cucumber_disease_classification. This is the largest individual release to-date of datasets. Specifically, 10+ datasets designed for disease classification have been introduced, alongside a variety of publicly-sourced object detection datasets.
Documentation
New documentation has been introduced for AgML. At the moment, it provides an interface for inspecting data online with ease, and will expand to include more information about library usage in general. Check out the documentation at: https://project-agml.github.io/AgML/index.html.
Major Updates
- The
agml.syntheticAPI has been improved and is now tested to work on Windows, in addition to Mac and Linux. Breaking changes that had been introduced into Helios have now been integrated into the AgML API as well. - The Raditation API that is introduced in Helios, for more accurate and efficient synthetic data generation, has also been incorporated into AgML in an early stage.
Quality Changes
- New tools for testing and uploading datasets, as well as version management on PyPi have been introduced.
- Code quality has been improved throughout the library, improving readability.
More Detailed Information
- Dev by @amogh7joshi in #58
- Add Radiation Project by @smbanx in #59
- pyproject_toml and use uv to sync deps. by @lalmei in #60
- feat/tests by @lalmei in #61
- Add format and linter by @lalmei in #62
- add documentaiton config init by @lalmei in #63
- release draft fix by @lalmei in #64
- docs:hot-fix by @lalmei in #65
- fix lesser filter by @lalmei in #67
- Feat/config test by @lalmei in #68
- New Datasets [Feb 2025] by @naitikjain3071 in #70
- AgML 0.7.1 Changes by @amogh7joshi in #71
New Contributors
- @naitikjain3071 made their first contribution in #70
Full Changelog: v0.7.0...v0.7.2
