Fish Disease Classification Model
This repository contains a model trained for classifying various fish diseases using Hugging Face's Transformers library. The model is trained to classify the following fish diseases:
- Tumor and deformity attack
- Polydactyly
- Hydrocephalus and swim bladder
- Holes in the head
- Nopez (I couldn't find a direct translation, it seems like a term specific to a certain context)
- Parasite in the mouth
- Catfish burn
- Gills
- Lernea worm
- Fungi
- Ich white spot
- Blind eye
- Fin rot
- Healthy
Dataset
The model is trained on a diverse dataset containing images of fish affected by different diseases as well as healthy fish samples. The dataset is labeled with the aforementioned disease categories to facilitate supervised training.
Model Architecture
The classification model is built upon state-of-the-art deep learning architecture, leveraging the power of convolutional neural networks (CNNs) for image classification tasks. It utilizes transfer learning techniques, starting with a pre-trained backbone network (e.g., ResNet, EfficientNet) and fine-tuning it on the fish disease dataset to adapt to the specific classification task.
Happy classifying fish diseases! 🐟🔍
