--- dataset_info: features: - name: image dtype: image - name: objects struct: - name: bbox list: list: int64 - name: categories list: class_label: names: '0': Corn leaf blight '1': Tomato Early blight leaf '2': Potato leaf early blight '3': Potato leaf late blight '4': Blueberry leaf '5': grape leaf black rot '6': Bell_pepper leaf spot '7': Cherry leaf '8': Peach leaf '9': Soyabean leaf '10': Strawberry leaf '11': Apple Scab Leaf '12': Corn rust leaf '13': Apple leaf '14': Corn Gray leaf spot '15': Tomato leaf mosaic virus '16': Tomato mold leaf '17': Tomato leaf yellow virus '18': Tomato leaf bacterial spot '19': Tomato leaf late blight '20': Squash Powdery mildew leaf '21': Bell_pepper leaf '22': grape leaf '23': Apple rust leaf '24': Tomato Septoria leaf spot '25': Tomato leaf '26': Raspberry leaf '27': Potato leaf '28': Tomato two spotted spider mites leaf splits: - name: train num_bytes: 1027346536 num_examples: 2346 download_size: 975874080 dataset_size: 1027346536 configs: - config_name: default data_files: - split: train path: data/train-* --- # Plant Doc Detection A dataset for object detection of various plant leaf diseases. The dataset contains 2,346 images with 8,435 bounding box annotations across 29 categories. This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library. ## 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}, 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}, series = {CoDS COMAD 2020} } ```