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Urban Street: Leaf Classification Dataset

21127501952
Tagenvironmental, biology
Taskclassification
Release YearMade in 2022
LicenseGNU LGPL 3.0
Download14 GB

Introduction #

Released 2022-09-24 ·Tingting Yang, Suyin Zhou, Zhijie Huanget al.

Authors introduce the Leaf component for classification task within The Tree Dataset of Urban Street, encompassing 21,127 high-resolution images distributed across 50 classes. With these comprehensive resources at your disposal, this subset empowers researchers and practitioners to delve deep into the detailed analysis of urban street greenery, offering a valuable resource for comprehensive instance segmentation studies. Automatic tree species identification can be used to realize autonomous street tree inventories and help people without botanical knowledge and experience to better understand the diversity and regionalization of different urban landscapes.

The Tree Dataset of Urban Street sub-datasets:

Classification:

Segmentation:

Detection:

image

Examples of Urban Street: Leaf (classification task).

About Tree Dataset of Urban Street:

Annotations were performed in a fine-grained manner by using polygons (bitmap in supervisely) to outline individual objects. Authors assessed the performance of various vision algorithms on different classification and segmentation tasks, including tree species identification and instance segmentation.

The proposed dataset was designed to capture urban street trees with subtropical or temperate monsoon climates in China. Our data collection and annotation methods were carefully created to capture the high variability of street trees. From February to October 2022, tens of thousands of tree images were acquired with mobile devices, covering spring, summer, fall and winter in 10 cities.

Similar to Cityscapes (Cordts et al., 2016) (available on DatasetNinja) and ADE20K (Zhou et al., 2019) (available on DatasetNinja), authors divide each organ dataset into separate training (train), validation (val) and test (test) sets.

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Dataset LinkHomepageDataset LinkResearch PaperDataset LinkBlog PostDataset LinkGitHub

Summary #

Tree Dataset of Urban Street: Leaf Classification is a dataset for a classification task. It is used in the environmental industry.

The dataset consists of 21127 images with 0 labeled objects. There are 3 splits in the dataset: train (16918 images), val (2117 images), and test (2092 images). Alternatively, the dataset could be split into 50 classification image sets: koelreuteria_paniculata (513 images), aesculus_chinensis (508 images), malushalliana (492 images), cinnamomum_camphora_(linn)_presl (490 images), liriodendron_chinense (486 images), lagerstroemia_indica (481 images), prunus_cerasifera_f._atropurpurea (481 images), aucuba_japonica_var._variegata (478 images), liquidambar_formosana (476 images), ginkgo_biloba (473 images), elaeocarpus_decipiens (471 images), flowering_cherry (469 images), platanus (467 images), triadica_sebifera (467 images), albizia_julibrissin (462 images), photinia_serratifolia (460 images), euonymus_japonicus_aureo_marginatus (457 images), magnolia_grandiflora_l (457 images), ligustrum_lucidum (456 images), nandina_domestica (456 images), osmanthus_fragrans (456 images), euonymus_japonicus (452 images), celtis_sinensis (451 images), styphnolobium_japonicum (450 images), michelia_chapensis (445 images), nerium_oleander_l (441 images), camptotheca_acuminata (438 images), prunus_persica (436 images), magnolia_liliflora_desr (430 images), zelkova_serrata (426 images), salix_babylonica (423 images), podocarpus_macrophyllus (413 images), llex_cornuta (410 images), loropetalum_chinense_var._rubrum (410 images), populus_l (408 images), viburnum_odoratissimum (407 images), pittosporum_tobira (405 images), acer_palmatum (401 images), platycladus_orientalis_beverlevensis (386 images), sapindus_saponaria (380 images), sabina_chinensis_cv._pyramidalis (372 images), michelia_figo_(lour.)_spreng (369 images), pinus_parviflora (359 images), rhododendron__pulchrum (344 images), buxus_sinica_var._parvifolia (317 images), metasequoia_glyptostroboides (312 images), juniperus_chinensis_kaizuca (295 images), taxodium_ascendens_brongn (286 images), cedrus_deodara (262 images), and pinus_massoniana_lamb (243 images). The dataset was released in 2022 by the Zhejiang Agriculture and Forestry University.

Here are the visualized examples for the classes:

Explore #

Urban Street: Leaf Classification dataset has 21127 images. Click on one of the examples below or open "Explore" tool anytime you need to view dataset images with annotations. This tool has extended visualization capabilities like zoom, translation, objects table, custom filters and more. Hover the mouse over the images to hide or show annotations.

OpenSample annotation mask from Urban Street: Leaf ClassificationSample image from Urban Street: Leaf Classification
OpenSample annotation mask from Urban Street: Leaf ClassificationSample image from Urban Street: Leaf Classification
OpenSample annotation mask from Urban Street: Leaf ClassificationSample image from Urban Street: Leaf Classification
OpenSample annotation mask from Urban Street: Leaf ClassificationSample image from Urban Street: Leaf Classification
OpenSample annotation mask from Urban Street: Leaf ClassificationSample image from Urban Street: Leaf Classification
OpenSample annotation mask from Urban Street: Leaf ClassificationSample image from Urban Street: Leaf Classification
OpenSample annotation mask from Urban Street: Leaf ClassificationSample image from Urban Street: Leaf Classification
OpenSample annotation mask from Urban Street: Leaf ClassificationSample image from Urban Street: Leaf Classification
OpenSample annotation mask from Urban Street: Leaf ClassificationSample image from Urban Street: Leaf Classification
OpenSample annotation mask from Urban Street: Leaf ClassificationSample image from Urban Street: Leaf Classification
OpenSample annotation mask from Urban Street: Leaf ClassificationSample image from Urban Street: Leaf Classification
OpenSample annotation mask from Urban Street: Leaf ClassificationSample image from Urban Street: Leaf Classification
OpenSample annotation mask from Urban Street: Leaf ClassificationSample image from Urban Street: Leaf Classification
OpenSample annotation mask from Urban Street: Leaf ClassificationSample image from Urban Street: Leaf Classification
OpenSample annotation mask from Urban Street: Leaf ClassificationSample image from Urban Street: Leaf Classification
OpenSample annotation mask from Urban Street: Leaf ClassificationSample image from Urban Street: Leaf Classification
OpenSample annotation mask from Urban Street: Leaf ClassificationSample image from Urban Street: Leaf Classification
OpenSample annotation mask from Urban Street: Leaf ClassificationSample image from Urban Street: Leaf Classification
OpenSample annotation mask from Urban Street: Leaf ClassificationSample image from Urban Street: Leaf Classification
OpenSample annotation mask from Urban Street: Leaf ClassificationSample image from Urban Street: Leaf Classification
OpenSample annotation mask from Urban Street: Leaf ClassificationSample image from Urban Street: Leaf Classification
OpenSample annotation mask from Urban Street: Leaf ClassificationSample image from Urban Street: Leaf Classification
OpenSample annotation mask from Urban Street: Leaf ClassificationSample image from Urban Street: Leaf Classification
OpenSample annotation mask from Urban Street: Leaf ClassificationSample image from Urban Street: Leaf Classification
OpenSample annotation mask from Urban Street: Leaf ClassificationSample image from Urban Street: Leaf Classification
OpenSample annotation mask from Urban Street: Leaf ClassificationSample image from Urban Street: Leaf Classification
OpenSample annotation mask from Urban Street: Leaf ClassificationSample image from Urban Street: Leaf Classification
OpenSample annotation mask from Urban Street: Leaf ClassificationSample image from Urban Street: Leaf Classification
OpenSample annotation mask from Urban Street: Leaf ClassificationSample image from Urban Street: Leaf Classification
OpenSample annotation mask from Urban Street: Leaf ClassificationSample image from Urban Street: Leaf Classification
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Have a look at 21127 images
View images along with annotations and tags, search and filter by various parameters

License #

Tree Dataset of Urban Street: Leaf Classification is under GNU LGPL 3.0 license.

Source

Citation #

If you make use of the Urban Street: Leaf Classification data, please cite the following reference:

@dataset{Urban Street: Leaf Classification,
  author={Tingting Yang and Suyin Zhou and Zhijie Huang and Aijun Xu and Junhua Ye and Jianxin Yin},
  title={Tree Dataset of Urban Street: Leaf Classification},
  year={2022},
  url={https://ytt917251944.github.io/dataset_jekyll/}
}

Source

If you are happy with Dataset Ninja and use provided visualizations and tools in your work, please cite us:

@misc{ visualization-tools-for-urban-street-leaf-classification-dataset,
  title = { Visualization Tools for Urban Street: Leaf Classification Dataset },
  type = { Computer Vision Tools },
  author = { Dataset Ninja },
  howpublished = { \url{ https://datasetninja.com/urban-street-leaf-classification } },
  url = { https://datasetninja.com/urban-street-leaf-classification },
  journal = { Dataset Ninja },
  publisher = { Dataset Ninja },
  year = { 2024 },
  month = { jul },
  note = { visited on 2024-07-27 },
}

Download #

Dataset Urban Street: Leaf Classification can be downloaded in Supervisely format:

As an alternative, it can be downloaded with dataset-tools package:

pip install --upgrade dataset-tools

… using following python code:

import dataset_tools as dtools

dtools.download(dataset='Urban Street: Leaf Classification', dst_dir='~/dataset-ninja/')

Make sure not to overlook the python code example available on the Supervisely Developer Portal. It will give you a clear idea of how to effortlessly work with the downloaded dataset.

The data in original format can be downloaded here.

. . .

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