Datasets:
File size: 1,945 Bytes
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dataset_info:
features:
- name: image
dtype: image
- name: label
dtype:
class_label:
names:
'0': atriplex
'1': chenopodium
'2': convolvulus
'3': cyperus
'4': datura
'5': lolium
'6': maize
'7': portulaca
'8': salsola
'9': solanum
'10': sorghum
'11': tomato
- name: crop
dtype: string
- name: growth_stage
dtype: string
splits:
- name: train
num_bytes: 95541077
num_examples: 55828
download_size: 642109490
dataset_size: 95541077
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
license: cc-by-4.0
task_categories:
- image-classification
size_categories:
- 10K<n<100K
---
# Maize Tomato Weed Classification
A dataset for classification of weeds and crops in maize and tomato fields. The dataset contains 55,828 images across 12 classes:
Images per class:
- atriplex: 2,459
- chenopodium: 3,375
- convolvulus: 2,302
- cyperus: 3,215
- datura: 1,271
- lolium: 1,063
- maize: 25,273
- portulaca: 2,052
- salsola: 2,409
- solanum: 4,084
- sorghum: 1,703
- tomato: 6,622
This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
## Citation
```bibtex
@article{mesias2025drone,
title={Drone imagery dataset for early-season weed classification in maize and tomato crops},
author={Mes{\'\i}as-Ruiz, Gustavo A and Pe{\~n}a, Jos{\'e} M and de Castro, Ana I and Dorado, Jos{\'e}},
journal={Data in Brief},
volume={58},
pages={111203},
year={2025},
publisher={Elsevier}
}
```
Mesías-Ruiz, G. A., Peña Barragán, J. M., Castro, A. I. D., & Dorado, J. (2024). DIWEED: Drone Imagery dataset for early-season WEED classification [Data set]. DIGITAL.CSIC. http://doi.org/10.20350/DIGITALCSIC/16559
*This dataset was reformatted from its original format to match HuggingFace standards.* |