Datasets:
File size: 2,099 Bytes
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dataset_info:
features:
- name: image
dtype: image
- name: bbch_stage
dtype: string
- name: label
dtype:
class_label:
names:
'0': Amaranthus_retroflexus (AMARE)
'1': Amaranthus_tuberculatus (AMATU)
'2': Chenopodium_album (CHEAL)
'3': Echinochloa_crus-galli (ECHCG)
'4': Setaria_faberi (SETFA)
splits:
- name: train
num_bytes: 377491661
num_examples: 3920
download_size: 379048807
dataset_size: 377491661
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
license: cc-by-4.0
task_categories:
- image-classification
size_categories:
- 1K<n<10K
---
# Wpdv2 Bbch Classification
This dataset provides real-world RGB images of agricultural weeds annotated using the BBCH growth stage classification system. It captures diverse weed species under typical field conditions relevant to precision agriculture applications. The images serve as a foundation for developing computer vision models focused on weed identification in crop environments. The dataset contains 3,920 images across 5 classes: Amaranthus_retroflexus (AMARE), Amaranthus_tuberculatus (AMATU), Chenopodium_album (CHEAL), Echinochloa_crus-galli (ECHCG), Setaria_faberi (SETFA).
Images per class:
- Amaranthus_retroflexus (AMARE): 934
- Amaranthus_tuberculatus (AMATU): 409
- Chenopodium_album (CHEAL): 832
- Echinochloa_crus-galli (ECHCG): 768
- Setaria_faberi (SETFA): 977
This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
## Citation
```bibtex
@article{fontaine2026taxonomical,
title={Taxonomical loss for weed seedlings image classification},
author={Fontaine, Hans-Olivier and Foucher, Samuel and Fallon, Edith and Simard, Marie-Jos{\'e}e and Lord, Etienne},
journal={Scientific Reports},
volume={16},
number={1},
pages={3837},
year={2026},
publisher={Nature Publishing Group UK London}
}
```
https://github.com/etiennelord/TaxonomicalLoss
*This dataset was reformatted from its original format to match HuggingFace standards.*
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