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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.
+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.
+
+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.
+## Installation
+
+To install the latest release of AgML, run the following command:
+
+```shell
+pip install agml
+```
+## Quick Start
+
+The following code allows you to list available datasets within the iNatAg dataset:
+```python
+# List iNatAg species
+import agml
+print(agml.data.public_data_sources(parent_dataset='iNatAg'))
+```
+
+In line with our vision of providing data across the entire taxonomic hierarchy, we also provide the ability to load data specifically according to family or species, or even common name:
+```python
+# Load a collection by family names
+loader = agml.data.AgMLDataLoader.from_parent("iNatAg", filters={"family_name": ["...", "..."]})
+
+# Load by common names
+loader = agml.data.AgMLDataLoader.from_parent("iNatAg", filters={"common_name": "..."})
+```