| --- |
| license: mit |
| library_name: pytorch |
| pipeline_tag: image-classification |
| tags: |
| - skin-disease |
| - medical-imaging |
| - cnn |
| - deep-learning |
| - healthcare |
| --- |
| |
| # Skin Diseases Detection Model (DermaDL) |
|
|
| ## Overview |
| DermaDL is a deep learning–based **skin disease detection model** trained on dermoscopic images. |
| It uses a **Convolutional Neural Network (CNN)** to classify multiple skin conditions and is intended for **research, educational, and prototype applications**. |
|
|
| > ⚠️ **Disclaimer:** This model is NOT a medical diagnostic tool and should not be used as a substitute for professional medical advice. |
|
|
| --- |
|
|
| ## Model Details |
| - **Task:** Image Classification |
| - **Architecture:** CNN with Transfer Learning |
| - **Framework:** PyTorch |
| - **Input Size:** 224 × 224 RGB images |
| - **Accuracy:** ~91% (validation set) |
|
|
| --- |
|
|
| ## Supported Skin Conditions |
| - Melanoma |
| - Basal Cell Carcinoma |
| - Squamous Cell Carcinoma |
| - Benign Keratosis |
| - Actinic Keratosis |
| - Dermatofibroma |
| - Vascular Lesions |
| - Nevus |
|
|
| *(Class labels may vary depending on dataset version)* |
|
|
| --- |
|
|
| ## Training Information |
| - **Dataset:** Public dermoscopic skin lesion datasets |
| - **Loss Function:** Cross-Entropy Loss |
| - **Optimizer:** Adam |
| - **Evaluation Metric:** Accuracy |
| - **Data Augmentation:** Rotation, flipping, normalization |
|
|
| --- |
|
|
| ## How to Use |
|
|
| ### 1️⃣ Install Dependencies |
| ```bash |
| pip install torch torchvision pillow |
| |
