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--- |
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license: cc-by-sa-4.0 |
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task_categories: |
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- object-detection |
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language: |
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- en |
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tags: |
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- object detection |
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- vision |
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size_categories: |
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- 1K<n<10K |
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extra_gated_heading: "Acknowledge license to accept the repository" |
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extra_gated_button_content: "Acknowledge license" |
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extra_gated_fields: |
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I agree to attribute the creator of this repository: checkbox |
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--- |
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--- |
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## Cashew Disease Identication with Artificial Intelligence (CADI-AI) Dataset |
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This repository contains a comprehensive dataset of cashew images captured by drones, accompanied by meticulously annotated labels. |
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Each high-resolution image in the dataset has a resolution of 1600x1300 pixels, providing fine details for analysis and model training. |
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To facilitate efficient object detection, each image is paired with a corresponding text file in YOLO format. |
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The YOLO format file contains annotations, including class labels and bounding box coordinates. |
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### Dataset Labels |
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``` |
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['abiotic', 'insect', 'disease'] |
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``` |
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### Number of Images |
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```json |
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{'train': 3788, 'valid': 710, 'test': 238} |
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``` |
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### Number of Instances Annotated |
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```json |
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{'insect':1618, 'abiotic':13960, 'disease':7032} |
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``` |
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### Folder structure after unzipping repective folders |
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```markdown |
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Data/ |
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└── train/ |
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├── images |
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├── labels |
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└── val/ |
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├── images |
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├── labels |
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└── test/ |
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├── images |
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├── labels |
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``` |
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### Dataset Information |
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The dataset was created by a team of data scientists from the KaraAgro AI Foundation, |
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with support from agricultural scientists and officers. |
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The creation of this dataset was made possible through funding of the |
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Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) through their projects |
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[Market-Oriented Value Chains for Jobs & Growth in the ECOWAS Region (MOVE)](https://www.giz.de/en/worldwide/108524.html) and |
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[FAIR Forward - Artificial Intelligence for All](https://www.bmz-digital.global/en/overview-of-initiatives/fair-forward/), which GIZ implements on |
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behalf the German Federal Ministry for Economic Cooperation and Development (BMZ). |
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For detailed information regarding the dataset, we invite you to explore the accompanying datasheet available [here](https://drive.google.com/file/d/1viv-PtZC_j9S_K1mPl4R1lFRKxoFlR_M/view?usp=sharing). |
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This comprehensive resource offers a deeper understanding of the dataset's composition, variables, data collection methodologies, and other relevant details. |
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