Silkworm_Diseases_Dataset

Description

Total Images: 5,529 Disease/Health Classes: Healthy, Pebrine, Grasserie,Flacherie Target: Overlapping silkworms,Healthy, Pebrine, Grasserie, Flacherie Applications: Disease classification, object detection, instance segmentation, silkworm counting, and health monitoring. This dataset contains images of silkworms categorized into five classes: Flacherie, Grasserie, Healthy Silkworm, Overlap, and Pebrine. The images are organized into training, testing, and split subsets to support machine-learning-based silkworm disease classification. The dataset is intended for research and development of computer vision and deep learning models for automated silkworm disease identification.

Steps to reproduce

Steps to Download and Use the Dataset 1. Download the ZIP file 'Silkworm_Disease_Classification_Dataset_Mendeley' from the Mendeley Data repository. 2. Extract the ZIP file to access the dataset folders. 3. The dataset contains five classes: Flacherie, Grasserie, Healthy_Silkworm, Overlap, and Pebrine 4. Each class folder contains three subsets: train, test, and split 5. The train folder is used for model training, while the test folder is used for independent evaluation. 6. The folder name represents the corresponding class label and can be used directly for image classification. 7. The extracted images can be loaded using standard Python image-processing/deep-learning libraries for further analysis.

Institutions

• Symbiosis International University

  Maharashtra, Pune

Categories

Licence