{
    "data_id": "44249",
    "name": "Meta_Album_PLT_NET_Micro",
    "exact_name": "Meta_Album_PLT_NET_Micro",
    "version": 1,
    "version_label": null,
    "description": "## **Meta-Album PlantNet Dataset (Micro)**\n***\nMeta-Album PlantNet dataset is created by sampling the Pl@ntNet-300k dataset (https:\/\/openreview.net\/forum?id=eLYinD0TtIt), itself a sampling of the Pl@ntNet Project's repository. The images and labels which enter this database are sourced by citizen botanists from around the world, then confirmed using a weighted reliability score from others users, such that each image has been reviewed by 2.03 citizen botanists on average. Of the 1 081 classes in the original Pl@ntNet-300k dataset, PLT_NET retains the 25 most populous classes, belonging to 21 genera, for a total of 120 688 images total, with min 2 914, max 9 011 image distribution per class. Each image contains a colored 128x128 image of a plant or a piece or a plant from the corresponding class (or in some cases sketches of plants or plant cells on microscope slides), scaled from the initial variable width using the INTER_AREA anti-aliasing filter from Open-CV. Almost all images were initially square; cropping by taking the largest possible square with center at the middle of the initial image was applied otherwise.  \n\n\n\n### **Dataset Details**\n![](https:\/\/meta-album.github.io\/assets\/img\/samples\/PLT_NET.png)\n\n**Meta Album ID**: PLT.PLT_NET  \n**Meta Album URL**: [https:\/\/meta-album.github.io\/datasets\/PLT_NET.html](https:\/\/meta-album.github.io\/datasets\/PLT_NET.html)  \n**Domain ID**: PLT  \n**Domain Name**: Plants  \n**Dataset ID**: PLT_NET  \n**Dataset Name**: PlantNet  \n**Short Description**: Plants Dataset with different species of plants  \n**\\# Classes**: 20  \n**\\# Images**: 800  \n**Keywords**: ecology, plants, plant species  \n**Data Format**: images  \n**Image size**: 128x128  \n\n**License (original data release)**: Creative Commons Attribution 4.0 International  \n**License URL(original data release)**: https:\/\/zenodo.org\/record\/4726653\nhttps:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode\n \n**License (Meta-Album data release)**: Creative Commons Attribution 4.0 International  \n**License URL (Meta-Album data release)**: [https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode](https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode)  \n\n**Source**: PlantNet  \n**Source URL**: https:\/\/plantnet.org\/en\/2021\/03\/30\/a-plntnet-dataset-for-machine-learning-researchers\/  \n  \n**Original Author**: Garcin, Camille and Joly, Alexis and Bonnet, Pierre and Lombardo, Jean-Christophe and Affouard, Antoine and Chouet, Mathias and Servajean, Maximilien and Salmon, Joseph and Lorieul, Titouan  \n**Original contact**: camille.garcin@inria.fr  \n\n**Meta Album author**: Felix Herron  \n**Created Date**: 01 March 2022  \n**Contact Name**: Ihsan Ullah  \n**Contact Email**: meta-album@chalearn.org  \n**Contact URL**: [https:\/\/meta-album.github.io\/](https:\/\/meta-album.github.io\/)  \n\n\n\n### **Cite this dataset**\n```\n@inproceedings{garcin2021plntnetk,\n    title={Pl@ntNet-300K: a plant image dataset with high label ambiguity and a long-tailed distribution},\n    author={Camille Garcin and alexis joly and Pierre Bonnet and Antoine Affouard and Jean-Christophe Lombardo and Mathias Chouet and Maximilien Servajean and Titouan Lorieul and Joseph Salmon},\n    booktitle={Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2)},\n    year={2021},\n    url={https:\/\/openreview.net\/forum?id=eLYinD0TtIt}\n}\n```\n\n\n### **Cite Meta-Album**\n```\n@inproceedings{meta-album-2022,\n        title={Meta-Album: Multi-domain Meta-Dataset for Few-Shot Image Classification},\n        author={Ullah, Ihsan and Carrion, Dustin and Escalera, Sergio and Guyon, Isabelle M and Huisman, Mike and Mohr, Felix and van Rijn, Jan N and Sun, Haozhe and Vanschoren, Joaquin and Vu, Phan Anh},\n        booktitle={Thirty-sixth Conference on Neural Information Processing Systems Datasets and Benchmarks Track},\n        url = {https:\/\/meta-album.github.io\/},\n        year = {2022}\n    }\n```\n\n\n### **More**\nFor more information on the Meta-Album dataset, please see the [[NeurIPS 2022 paper]](https:\/\/meta-album.github.io\/paper\/Meta-Album.pdf)  \nFor details on the dataset preprocessing, please see the [[supplementary materials]](https:\/\/openreview.net\/attachment?id=70_Wx-dON3q&name=supplementary_material)  \nSupporting code can be found on our [[GitHub repo]](https:\/\/github.com\/ihsaan-ullah\/meta-album)  \nMeta-Album on Papers with Code [[Meta-Album]](https:\/\/paperswithcode.com\/dataset\/meta-album)  \n\n\n\n### **Other versions of this dataset**\n[[Mini]](https:\/\/www.openml.org\/d\/44293)  [[Extended]](https:\/\/www.openml.org\/d\/44327)  ",
    "format": "arff",
    "uploader": "Meta Album",
    "uploader_id": 30980,
    "visibility": "public",
    "creator": "\"Ihsan Ullah\"",
    "contributor": null,
    "date": "2022-10-12 15:35:12",
    "update_comment": null,
    "last_update": "2022-10-12 15:35:12",
    "licence": "CC BY-NC 4.0",
    "status": "active",
    "error_message": null,
    "url": "https:\/\/api.openml.org\/data\/download\/22109930\/dataset",
    "kaggle_url": null,
    "default_target_attribute": "CATEGORY",
    "row_id_attribute": null,
    "ignore_attribute": null,
    "runs": 0,
    "suggest": {
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            "## **Meta-Album PlantNet Dataset (Micro)** Meta-Album PlantNet dataset is created by sampling the Pl@ntNet-300k dataset (https:\/\/openreview.net\/forum?id=eLYinD0TtIt), itself a sampling of the Pl@ntNet Project's repository. The images and labels which enter this database are sourced by citizen botanists from around the world, then confirmed using a weighted reliability score from others users, such that each image has been reviewed by 2.03 citizen botanists on average. Of the 1 081 classes in the "
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    "qualities": {
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        "NumberOfMissingValues": 800,
        "NumberOfInstancesWithMissingValues": 800,
        "NumberOfNumericFeatures": 1,
        "NumberOfSymbolicFeatures": 0,
        "PercentageOfBinaryFeatures": 0,
        "PercentageOfInstancesWithMissingValues": 100,
        "PercentageOfMissingValues": 33.33333333333333,
        "AutoCorrelation": 1,
        "PercentageOfNumericFeatures": 33.33333333333333,
        "Dimensionality": 0.00375,
        "PercentageOfSymbolicFeatures": 0,
        "MajorityClassPercentage": 5,
        "MajorityClassSize": 40,
        "MinorityClassPercentage": 5,
        "MinorityClassSize": 40,
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    "tags": [],
    "features": [
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