"Unlock the power of AI with Smart Detection – the ultimate acne detection app. Harness cutting-edge AI and ICP technology to quickly and efficiently assess your skin's condition."

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Smart Acne Detection is a smart acne detection application developed using React.js for the frontend and Kybra Python for the backend, with Internet Computer Protocol (ICP) based storage. This application allows users to detect six types of acne through analysis of captured images from the camera or uploaded using AI technology. Smart Acne Detection can detect user acne and display data on detected acne. Users log in to the application using Internet Identity, adding another layer of security extra. For monetization, this application limits detection access to 5 times at the start. After that, users must subscribe to premium to continue using the service detect and access skin care tips. The combined use of AI and ICP makes this application fast, accurate and safe.

To learn more, see the available internet computer documents:

• Quick Start
• SDK Developer Tools
• Kybra Book

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• Acne Type Detection: Detects and classifies six types of acne different.
• Image Analysis: Using deep learning technology to detect from the camera or upload image.
• Internet Identity: To access login with ICP.
• Premium Subscription: Access detection without limitations.
• Care Tips Menu: Tips for facial skin care.

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• dfx 0.20.1
• Backend: kybra 0.6.0
• Frontend: Node Version 18 & vite
• AI: YoloV8
• Auth: Internet Identity

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To run this project in local, you can use the following commands:

1. Running dfx for create replica

# Starts the replica, running in the background
dfx start --background

2. Acivate enviroment

#activate environment has been installed package
source env/bin/activate

3. Deploy canister

# Deploys your canisters to the replica and generates your candid interface
dfx deploy

4. Insert data subcribes package

dfx canister call AcneDetection_backend insert_subscribe_packages

5. Install package frontend

npm install

6. Running frontend canister

nmp run start

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1. Leader and Backend Developer : Arin Cantika Musi
2. Frontend Developer : Puji Dhiya Nabila
3. AI Developer : Vicki Azwar

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If any questions occured, or in the need of any discussion or details, please contact use:

• email: arincantikam@gmail.com

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