ahmetkasif/fishlens

Dataset Labels

['aeromonas septicemia', 'columnaris disease', 'edwardsiella ictaluri -bacterial red disease-', 'epizootic ulcerative syndrome -eus-', 'flavobacterium -bacterial gill disease-', 'fungal disease -saprolegniasis-', 'healthy fish', 'ichthyophthirius -white spots-', 'parasitic disease', 'streptococcus', 'tilapia lake virus -tilv-']

Number of Images

{'valid': 472, 'test': 464, 'train': 6564}

How to Use

• Install datasets:

pip install datasets

• Load the dataset:

from datasets import load_dataset

ds = load_dataset("ahmetkasif/fishlens", name="full")
example = ds['train'][0]

Roboflow Dataset Page

https://universe.roboflow.com/fishlens/fishlens-modelv1/dataset/2

Citation

@misc{
                            fishlens-modelv1_dataset,
                            title = { fishlens-modelv1 Dataset },
                            type = { Open Source Dataset },
                            author = { fishlens },
                            howpublished = { \\url{ https://universe.roboflow.com/fishlens/fishlens-modelv1 } },
                            url = { https://universe.roboflow.com/fishlens/fishlens-modelv1 },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2024 },
                            month = { sep },
                            note = { visited on 2024-12-05 },
                            }

License

CC BY 4.0

Dataset Summary

This dataset was exported via roboflow.com on September 9, 2024 at 8:30 AM GMT

Roboflow is an end-to-end computer vision platform that helps you

• collaborate with your team on computer vision projects
• collect & organize images
• understand and search unstructured image data
• annotate, and create datasets
• export, train, and deploy computer vision models
• use active learning to improve your dataset over time

For state of the art Computer Vision training notebooks you can use with this dataset, visit https://github.com/roboflow/notebooks

To find over 100k other datasets and pre-trained models, visit https://universe.roboflow.com

The dataset includes 7500 images. Fish-skin-diseases are annotated in COCO format.

The following pre-processing was applied to each image:

• Auto-orientation of pixel data (with EXIF-orientation stripping)
• Resize to 640x640 (Fit within)
• Auto-contrast via histogram equalization

The following augmentation was applied to create 3 versions of each source image:

• Equal probability of one of the following 90-degree rotations: none, clockwise, counter-clockwise, upside-down
• Random rotation of between -45 and +45 degrees
• Random brigthness adjustment of between -15 and +15 percent
• Random exposure adjustment of between -15 and +15 percent
• Salt and pepper noise was applied to 0.1 percent of pixels