datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
task_book_leavesThis dataset was created using LeRobot.
Dataset Structure
meta/info.json:
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"features": {… See the full description on the dataset page: https://huggingface.co/datasets/rli14/task_book_leaves.task_pour_leavesThis dataset was created using LeRobot.
Dataset Structure
meta/info.json:
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"features": {… See the full description on the dataset page: https://huggingface.co/datasets/rli14/task_pour_leaves.task_pull_leavesThis dataset was created using LeRobot.
Dataset Structure
meta/info.json:
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"features": {… See the full description on the dataset page: https://huggingface.co/datasets/rli14/task_pull_leaves.Coffee_leaves_sections_FO
Dataset Card for coffee_leaves_anomalib_2
This is a FiftyOne dataset with 35962 samples.
Installation
If you haven't already, install FiftyOne:
pip install -U fiftyone
Usage
import fiftyone as fo
from fiftyone.utils.huggingface import load_from_hub
# Load the dataset
# Note: other available arguments include 'max_samples', etc
dataset = load_from_hub("pjramg/Coffee_leaves_sections_FO")
# Launch the App
session = fo.launch_app(dataset)… See the full description on the dataset page: https://huggingface.co/datasets/pjramg/Coffee_leaves_sections_FO.leaves-of-grass
leaves of grass
The following is a dataset for training a model to generate text in the style of Walt Whitman's "Leaves of Grass".
The idea with this dataset is to provide a single line (input) and then provide the next lines (1 to 10 lines) of the poem as output.
A model can then be trained to generate lines of poems given a single line of input.
There is a generate_data.py script that can be used to generate the dataset.
It keeps some formatting. New lines may be indented by a… See the full description on the dataset page: https://huggingface.co/datasets/diversen/leaves-of-grass.tomato-leaves-dataset
Tomato Leaves Dataset
Overview
This dataset contains images of tomato leaves categorized into different classes based on the type of disease or health condition. The dataset is divided into training, validation, and test sets, with a ratio of 8:1:1. The classes include various diseases as well as healthy leaves. The dataset includes both augmented and non-augmented images.
Dataset Structure
The dataset is organized into three main splits:
train
validation
test… See the full description on the dataset page: https://huggingface.co/datasets/lorenzoxi/tomato-leaves-dataset.tomato-leaves-dataset
Tomato Leaves Dataset
Overview
This dataset contains images of tomato leaves categorized into different classes based on the type of disease or health condition. The dataset is divided into training, validation, and test sets, with a ratio of 8:1:1. The classes include various diseases as well as healthy leaves. The dataset includes both augmented and non-augmented images.
Dataset Structure
The dataset is organized into three main splits:
train… See the full description on the dataset page: https://huggingface.co/datasets/shreemunale/tomato-leaves-dataset.Indian-plant-leaves-species
Indian Plant Leaves Species
Dataset Summary
This dataset consists of 592 high-resolution images of leaves from 12 different plant species. All images were captured using a mobile phone camera under natural lighting conditions. The dataset is intended for use in plant species classification, leaf recognition, and related computer vision tasks.
Supported Tasks and Leaderboards
Image Classification
Species Recognition
Transfer Learning for Plant Identification… See the full description on the dataset page: https://huggingface.co/datasets/avaishnav/Indian-plant-leaves-species.medicinal_leavesmangrove-leavesmed_leaves
Dataset Card for "med_leaves"
More Information needed
tomato-leaves-dataset
Tomato Leaves Dataset
Overview
This dataset contains images of tomato leaves categorized into different classes based on the type of disease or health condition. The dataset is divided into training, validation, and test sets, with a ratio of 8:1:1. The classes include various diseases as well as healthy leaves. The dataset includes both augmented and non-augmented images.
Dataset Structure
The dataset is organized into three main splits:
train
validation
test… See the full description on the dataset page: https://huggingface.co/datasets/Vlone571/tomato-leaves-dataset.leaves-ph
Leaves.PH: Metro Manila tree-canopy series
Open per-LGU and per-barangay annual tree-canopy estimates for the 17 LGUs of
Metro Manila (2019 to 2026), measured from Sentinel-2 imagery with a
human-calibrated classifier. Canopy here is a dense-vegetation proxy, not a
pixel-exact tree census. Read each year as a cross-sectional snapshot, not a
validated change series.
What is in this repo
per_lgu/per_lgu_canopy_2019_2026.csv… See the full description on the dataset page: https://huggingface.co/datasets/xmpuspus/leaves-ph.tomato-leaves-dataset
Tomato Leaves Dataset
Overview
This dataset contains images of tomato leaves categorized into different classes based on the type of disease or health condition. The dataset is divided into training, validation, and test sets, with a ratio of 8:1:1. The classes include various diseases as well as healthy leaves. The dataset includes both augmented and non-augmented images.
Dataset Structure
The dataset is organized into three main splits:
train
validation
test… See the full description on the dataset page: https://huggingface.co/datasets/Masamawsom/tomato-leaves-dataset.Coffee_leaves_rocole_FO
Dataset Card for coffee_rocole_patches
This is a FiftyOne dataset with 2329 samples.
Installation
If you haven't already, install FiftyOne:
pip install -U fiftyone
Usage
import fiftyone as fo
from fiftyone.utils.huggingface import load_from_hub
# Load the dataset
# Note: other available arguments include 'max_samples', etc
dataset = load_from_hub("pjramg/Coffee_leaves_rocole_FO")
# Launch the App
session = fo.launch_app(dataset)
Dataset… See the full description on the dataset page: https://huggingface.co/datasets/pjramg/Coffee_leaves_rocole_FO.centella_asiatica_leaves
Centella Asiatica Leaves
A dataset for image classification of Centella Asiatica Leaves. The dataset contains 9,094 images across 3 classes: Dried, Healthy, Unhealthy.
Images per class:
Dried: 2,996
Healthy: 3,048
Unhealthy: 3,050
This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
Citation
@article{jadhav2024dataset,
title={Dataset of Centella Asiatica leaves for quality assessment and machine learning applications}… See the full description on the dataset page: https://huggingface.co/datasets/Project-AgML/centella_asiatica_leaves.Data_Orange_2_Leaves_augLeavestomato-leaves-dataset
Tomato Leaves Dataset
Overview
This dataset contains images of tomato leaves categorized into different classes based on the type of disease or health condition. The dataset is divided into training, validation, and test sets, with a ratio of 8:1:1. The classes include various diseases as well as healthy leaves. The dataset includes both augmented and non-augmented images.
Dataset Structure
The dataset is organized into three main splits:
train
validation
test… See the full description on the dataset page: https://huggingface.co/datasets/artup1/tomato-leaves-dataset.pick_green_tea_leaves1.4This dataset was created using LeRobot.
Dataset Structure
meta/info.json:
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"splits": {
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"data_path": "data/chunk-{chunk_index:03d}/file-{file_index:03d}.parquet",
"video_path":… See the full description on the dataset page: https://huggingface.co/datasets/zslingling123/pick_green_tea_leaves1.4.tomato-leaves-dataset
Tomato Leaves Dataset
Overview
This dataset contains images of tomato leaves categorized into different classes based on the type of disease or health condition. The dataset is divided into training, validation, and test sets, with a ratio of 8:1:1. The classes include various diseases as well as healthy leaves. The dataset includes both augmented and non-augmented images.
Dataset Structure
The dataset is organized into three main splits:
train
validation
test… See the full description on the dataset page: https://huggingface.co/datasets/laiba-farid-ml/tomato-leaves-dataset.pick_green_tea_leaves1.6This dataset was created using LeRobot.
Dataset Structure
meta/info.json:
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"splits": {
"train": "0:9"
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"data_path": "data/chunk-{chunk_index:03d}/file-{file_index:03d}.parquet",
"video_path":… See the full description on the dataset page: https://huggingface.co/datasets/zslingling123/pick_green_tea_leaves1.6.tomato-leaves-dataset
Tomato Leaves Dataset
Overview
This dataset contains images of tomato leaves categorized into different classes based on the type of disease or health condition. The dataset is divided into training, validation, and test sets, with a ratio of 8:1:1. The classes include various diseases as well as healthy leaves. The dataset includes both augmented and non-augmented images.
Dataset Structure
The dataset is organized into three main splits:
train
validation
test… See the full description on the dataset page: https://huggingface.co/datasets/lerando/tomato-leaves-dataset.white_grapes_and_leaves_segmentation
White Grapes And Leaves Segmentation
A dataset for semantic segmentation of White Grapes And Leaves. The dataset contains 273 images with pixel-level mask annotations.
This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
Citation
@inproceedings{kalampokas2020semantic,
title={Semantic segmentation of vineyard images using convolutional neural networks},
author={Kalampokas, Theofanis and Tziridis, Konstantinos and Nikolaou… See the full description on the dataset page: https://huggingface.co/datasets/Project-AgML/white_grapes_and_leaves_segmentation.red_grapes_and_leaves_segmentation
Red Grapes And Leaves Segmentation
A dataset for semantic segmentation of Red Grapes And Leaves Segmentation. The dataset contains 258 images with pixel-level mask annotations.
This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
Citation
@inproceedings{kalampokas2020semantic,
title={Semantic segmentation of vineyard images using convolutional neural networks},
author={Kalampokas, Theofanis and Tziridis, Konstantinos and… See the full description on the dataset page: https://huggingface.co/datasets/Project-AgML/red_grapes_and_leaves_segmentation.SAM_leavestomato-leaves-dataset
Tomato Leaves Dataset
Overview
This dataset contains images of tomato leaves categorized into different classes based on the type of disease or health condition. The dataset is divided into training, validation, and test sets, with a ratio of 8:1:1. The classes include various diseases as well as healthy leaves. The dataset includes both augmented and non-augmented images.
Dataset Structure
The dataset is organized into three main splits:
train
validation
test… See the full description on the dataset page: https://huggingface.co/datasets/codraja2006/tomato-leaves-dataset.leaves_or_notCotton_Leavestomato-leaves-dataset