marcelhuber/KermanyV3_resized

Dataset Structure

This dataset contains images categorized into different classes for medical image analysis. The dataset is organized as follows:

Data Split

The dataset is split into two main subsets: train and test.

Train Subset

The train subset contains images used for training machine learning models. It is further organized into subdirectories for each class.

• CNV: Contains 37,205 images.
• DME: Contains 11,348 images.
• DRUSEN: Contains 8,616 images.
• NORMAL: Contains 51,140 images.

Test Subset

The test subset contains images reserved for testing the trained models. It is organized in a similar manner to the train subset, with subdirectories for each class.

• CNV: Contains 250 images.
• DME: Contains 250 images.
• DRUSEN: Contains 250 images.
• NORMAL: Contains 250 images.

Usage

This dataset can be used for tasks such as classification, image recognition, and medical analysis. The provided class subdirectories indicate the different categories for the images.