| --- |
| license: cc-by-4.0 |
| dataset_info: |
| features: |
| - name: image_id |
| dtype: int64 |
| - name: image |
| dtype: image |
| - name: width |
| dtype: int64 |
| - name: height |
| dtype: int64 |
| - name: objects |
| struct: |
| - name: id |
| sequence: int64 |
| - name: area |
| sequence: int64 |
| - name: bbox |
| sequence: |
| sequence: float32 |
| - name: category |
| sequence: string |
| splits: |
| - name: train |
| num_bytes: 905619617.284 |
| num_examples: 2342 |
| - name: test |
| num_bytes: 73503583 |
| num_examples: 236 |
| download_size: 991825068 |
| dataset_size: 979123200.284 |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/train-* |
| - split: test |
| path: data/test-* |
| task_categories: |
| - object-detection |
| --- |
| |
|
|
| This Dataset is created from processing the files from this GitHub repository : PlantDoc-Object-Detection-Dataset |
|
|
| @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} |
| } |
|
|
