---
license: cc-by-4.0
task_categories:
- object-detection
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: test
    path: data/test-*
dataset_info:
  features:
  - name: image_id
    dtype: int64
  - name: image
    dtype: image
  - name: width
    dtype: int64
  - name: height
    dtype: int64
  - name: objects
    struct:
    - name: area
      sequence: int64
    - name: bbox
      sequence:
        sequence: int64
    - name: category
      sequence: int64
  - name: pixel_values
    sequence:
      sequence:
        sequence: float32
  - name: pixel_mask
    sequence:
      sequence: int64
  - name: labels
    struct:
    - name: area
      sequence: float32
    - name: boxes
      sequence:
        sequence: float32
    - name: class_labels
      sequence: int64
    - name: image_id
      sequence: int64
    - name: iscrowd
      sequence: int64
    - name: orig_size
      sequence: int64
    - name: size
      sequence: int64
  splits:
  - name: train
    num_bytes: 27853534555.06
    num_examples: 2110
  - name: test
    num_bytes: 2810816579.0
    num_examples: 214
  download_size: 5301851591
  dataset_size: 30664351134.06
---
This Dataset is created from processing the files from this GitHub repository : [PlantDoc-Object-Detection-Dataset](https://github.com/pratikkayal/PlantDoc-Object-Detection-Dataset/tree/master)


Citation

BibTeX:

```
@inproceedings{10.1145/3371158.3371196,
author = {Singh, Davinder and Jain, Naman and Jain, Pranjali and Kayal, Pratik and Kumawat, Sudhakar and Batra, Nipun},
title = {PlantDoc: A Dataset for Visual Plant Disease Detection},
year = {2020},
isbn = {9781450377386},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3371158.3371196},
doi = {10.1145/3371158.3371196},
booktitle = {Proceedings of the 7th ACM IKDD CoDS and 25th COMAD},
pages = {249–253},
numpages = {5},
keywords = {Deep Learning, Object Detection, Image Classification},
location = {Hyderabad, India},
series = {CoDS COMAD 2020}
}
```