---
license: apache-2.0
datasets:
- Nagabu/HAM10000
metrics:
- accuracy
pipeline_tag: image-classification
library_name: transformers
---

# Dermacare Skin Lesion Classification

Dermacare is a skin lesion classification model built using Keras. It classifies dermatoscopic images into various types of skin lesions, aiding in the early detection of skin cancer.

## Model Architecture
The model is a Convolutional Neural Network (CNN) trained on the [HAM10000 dataset](https://www.kaggle.com/datasets/ultralytics/ham10000) with the following key specifications:

- **Input**: 224x224 RGB images
- **Architecture**: Keras-based CNN
- **Output**: 7-class classification for different types of skin lesions

## Usage Example
To use the model for predictions, send an image to the inference endpoint as shown below:

```python
import requests

API_URL = "https://api-inference.huggingface.co/models/sreejith782/Dermacare_Skin_Lesion_classification"
headers = {"Authorization": "Bearer YOUR_HUGGING_FACE_TOKEN"}

response = requests.post(API_URL, headers=headers, files={"inputs": open("path_to_image.jpg", "rb")})
print(response.json())