File size: 1,526 Bytes
5ddaac8 2654726 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 |
---
license: gpl-3.0
---
# 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:
1. **Tumor and deformity attack**
2. **Polydactyly**
3. **Hydrocephalus and swim bladder**
4. **Holes in the head**
5. **Nopez (I couldn't find a direct translation, it seems like a term specific to a certain context)**
6. **Parasite in the mouth**
7. **Catfish burn**
8. **Gills**
9. **Lernea worm**
10. **Fungi**
11. **Ich white spot**
12. **Blind eye**
13. **Fin rot**
14. **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.
[dataset base](https://huggingface.co/datasets/jero98772/CuraPeces_Background)
[better dataset(removed background)](https://huggingface.co/datasets/jero98772/CuraPeces_Removed_background)
## 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! 🐟🔍 |