Datasets:
File size: 1,410 Bytes
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dataset_info:
features:
- name: image
dtype: image
- name: objects
struct:
- name: bbox
list:
list: float64
- name: categories
list:
class_label:
names:
'0': horseweed
'1': kochia
'2': corn
'3': ragweed
'4': redrootpigweed
splits:
- name: train
num_bytes: 811723383
num_examples: 3208
download_size: 1334656681
dataset_size: 811723383
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
license: cc-by-4.0
task_categories:
- object-detection
size_categories:
- 1K<n<10K
---
# ImageWeeds Weed Detection
A dataset for detection of weeds. The dataset contains 3,208 images with 6,932 bounding box annotations across 5 categories.
This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
## Citation
```bibtex
<!-- TODO: add BibTeX citation -->
```
Rai, Nitin; Villamil Mahecha, Maria; Christensen, Annika; Quanbeck, Jamison; Howatt, Kirk; Ostlie, Michael; Zhang, Yu; Sun, Xin (2023), “ImageWeeds: An Image dataset consisting of weeds in multiple formats to advance computer vision algorithms for real-time weed identification and spot spraying application”, Mendeley Data, V2, doi: 10.17632/8kjcztbjz2.2
*This dataset was reformatted from its original format to match HuggingFace standards.* |