A CNN-based skin disease classifier for dogs using MobileNetV2. It identifies four conditions—bacterial dermatosis, fungal infection, hypersensitivity dermatitis, and healthy—and suggests treatments based on veterinary best practices. Useful for early screening in low-resource settings.
# Dog-Skin-Disease-Detection and Treatment-Recommendation
This project aims to help identify common skin diseases in dogs using a convolutional neural network (CNN) model built with MobileNetV2. The system classifies images into four categories—bacterial dermatosis, fungal infection, hypersensitivity dermatitis, and healthy—and recommends a set of medications or treatments based on veterinary best practices. It is designed to assist in early screening of street dogs or pets, especially in resource-limited settings where veterinary access is delayed.
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## 🧠 Model Overview
- *Architecture*: Transfer learning using MobileNetV2
- *Classifier*: Multiclass softmax (4 skin condition classes)
- *Input*: Dog skin image
- *Output*: Predicted condition + suggested medicines
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## 🐶 Classes Covered
| Label | Description |
|-------------------------------|----------------------------------------|
| bacterial_dermatosis | Skin infections due to bacteria |
| fungal_infection | Includes yeast and ringworm |
| hypersensitivity_dermatitis | Allergic skin inflammation |
| healthy | No visible skin problems |
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## 💊 Treatment Suggestions
Each condition comes with a curated list of suggested treatments.
Here are examples:
### Bacterial Dermatosis
- Chlorhexidine 4% shampoo
- Cephalexin (oral antibiotic)
- Mupirocin ointment
### Fungal Infection
- Ketoconazole shampoo
- Itraconazole (oral)
- Miconazole spray
### Hypersensitivity Dermatitis
- Apoquel (Oclacitinib)
- Cytopoint injection
- Prednisone (short-term)
> ⚠ Always consult a veterinarian before applying medication.
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## 🗂 Dataset
- Name: [Dogs Skin Disease Dataset] (
kaggle.com)
- Source: Kaggle
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## 🛠️ Technologies Used
### 🖥️ Programming Language
- Python
### 📚 Libraries & Frameworks
- NumPy – Numerical operations …