metadata

title: Acne Detection AI 🔥
emoji: 🔥
colorFrom: indigo
colorTo: yellow
sdk: gradio
sdk_version: 5.25.2
app_file: app.py
pinned: true
license: apache-2.0
short_description: Advanced AI for Acne Segmentation & Severity Classification

🧠 Acne Detection & Classification with Deep Learning

This application demonstrates a powerful AI-driven pipeline for acne detection, segmentation, and severity classification, combining:

A UNet-based CNN for precise acne lesion segmentation (pixel-wise accuracy ≈ 96–98%)
A transformer-based classifier (fine-tuned Vision Transformer) for grading severity based on dermatological standards

Try it by uploading a face image.
It will return: ✅ a visual overlay showing detected acne regions
✅ a severity label (from clear skin to very severe acne)

🧪 Model Architecture

🔹 Segmentation Model

Architecture: UNet with ResNet34 backbone (from smp)
Optimized for: Binary mask prediction of acne regions
Trained on: Annotated dermatological datasets
Accuracy: Pixel Accuracy ≈ 98%, IoU ≈ 91%

🔹 Classification Model

Architecture: Vision Transformer (ViT)
Source: imfarzanansari/skintelligent-acne
Labels: From Level -1 (Clear) to Level 4 (Very Severe Acne)
Input: Facial image
Output: Severity level + confidence score

📈 Example Output

Input Image	Segmentation Overlay	Acne Level
		Level 2: Moderate Acne

💡 Use Cases

Dermatology research and screening
Skincare and cosmetic product testing
Automated health monitoring platforms

🧩 Tech Stack

PyTorch, Segmentation Models PyTorch
Transformers by Hugging Face
Albumentations for fast preprocessing
OpenCV, Gradio for live interface

🤖 Try it now!

Click below and upload a photo to get real-time predictions:

Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference