Tree Dataset of Urban Street: Leaf is a dataset for instance segmentation, semantic segmentation, object detection, and classification tasks. It is used in the environmental industry.

The dataset consists of 9763 images with 9791 labeled objects belonging to 39 different classes including leaf_of_cinnamomum_camphora_(linn)_presl, leaf_of_malushalliana, leaf_of_elaeocarpus_decipiens, and other: ligustrum_lucidum, leaf_of_koelreuteria_paniculata, leaf_of_michelia_chapensis, leaf_of_aesculus_chinensis, leaf_of_flowering_cherry, euonymus_japonicus, leaf_of_prunus_cerasifera_f._atropurpurea, leaf_of_triadica_sebifera, leaf_of_celtis_sinensis, leaf_of_salix_babylonica, leaf_of_photinia_serratifolia, leaf_of_platanus, leaf_of_magnolia_liliflora_desr, nandina_domestica, aucuba_japonica_var._variegata, leaf_of_styphnolobium_japonicum, euonymus_japonicus_aureo_marginatus, leaf_of_lagerstroemia_indica, leaf_of_liriodendron_chinense, leaf_of_camptotheca_acuminata, leaf_of_magnolia_grandiflora_l., leaf_of_sapindus_saponaria, viburnum_odoratissimum, leaf_of_zelkova_serrata, pittosporum_tobira, leaf_of_prunus_persica, michelia_figo_(lour.)_spreng, nerium_oleander_l., llex_cornuta, loropetalum_chinense_var._rubrum, leaf_of_populus_l., leaf_of_ginkgo_biloba, leaf_of_osmanthus_fragrans, leaf_of_liquidambar_formosana, leaf_of_acer_palmatum, and rhododendron_pulchrum.

Images in the Urban Street: Leaf dataset have pixel-level instance segmentation annotations. Due to the nature of the instance segmentation task, it can be automatically transformed into a semantic segmentation (only one mask for every class) or object detection (bounding boxes for every object) tasks. All images are labeled (i.e. with annotations). There are 3 splits in the dataset: train (7813 images), test (975 images), and val (975 images). Also, the dataset includes classification_tag. The dataset was released in 2022 by the Zhejiang Agriculture and Forestry University.

Here is a visualized example for randomly selected sample classes:

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

Source

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

@dataset{Urban Street: Leaf,
  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},
  year={2022},
  url={https://www.kaggle.com/datasets/erickendric/tree-dataset-of-urban-street-segmentation-leaf}
}

Source

Dataset Urban Street: Leaf 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', 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.