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  size_categories:
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  - 1K<n<10K
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  ---
 
 
 
 
 
 
 
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  ### Dataset Labels
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  ```json
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  {'insect':1618, 'abiotic':13960, 'disease':7032}
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- ```
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  size_categories:
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  ---
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+ ## Cashew Disease Identication with Artificial Intelligence (CADI-AI) Dataset
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+
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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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+
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  ### Dataset Labels
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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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+
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+ ```markdown
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+ Data/
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+ └── train/
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+ β”œβ”€β”€ images
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+ β”œβ”€β”€ labels
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+ └── val/
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+ β”œβ”€β”€ images
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+ β”œβ”€β”€ labels
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+ └── test/
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+ β”œβ”€β”€ images
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+ β”œβ”€β”€ labels
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+ ```
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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 fΓΌr Internationale Zusammenarbeit (GIZ) through their projects
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+ β€œMarket-Oriented Value Chains for Jobs & Growth in the ECOWAS Region (MOVE)” and
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+ "FAIR Forward - Artificial Intelligence for All", which GIZ implements on
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+ behalf the German Federal Ministry for Economic Cooperation and Development (BMZ).