Datasets:
Update README.md
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README.md
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iNatAg is a large-scale dataset derived from the iNaturalist dataset, designed for species classification and crop/weed classification in agricultural and ecological applications. It consists of 2,959 species with a breakdown of 1,986 crop species and 973 weed species.The dataset contains a total of 4,720,903 images, making it one of the largest and most diverse datasets available for plant species identification and classification.
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iNatAg is also released as part of the [AgML](https://github.com/Project-AgML/AgML) dataset collection, with support for filtering by species, genus, or family and direct data loading through a streamlined API.
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# Load by common names
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loader = agml.data.AgMLDataLoader.from_parent("iNatAg", filters={"common_name": "..."})
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```
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---
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license: apache-2.0
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task_categories:
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- image-classification
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language:
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- en
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tags:
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- agriculture
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- plant
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- crop
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- weed
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- farm
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- food
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size_categories:
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- 1M<n<10M
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---
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iNatAg is a large-scale dataset derived from the iNaturalist dataset, designed for species classification and crop/weed classification in agricultural and ecological applications. It consists of 2,959 species with a breakdown of 1,986 crop species and 973 weed species.The dataset contains a total of 4,720,903 images, making it one of the largest and most diverse datasets available for plant species identification and classification.
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iNatAg is also released as part of the [AgML](https://github.com/Project-AgML/AgML) dataset collection, with support for filtering by species, genus, or family and direct data loading through a streamlined API.
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# Load by common names
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loader = agml.data.AgMLDataLoader.from_parent("iNatAg", filters={"common_name": "..."})
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```
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