A K-Pop fan-driven platform for sharing artist photos.
IdolSnap is an Android application that allowed K-Pop fans to upload and share images of their favorite artists. The app leveraged machine learning and cloud services to enhance user experience, including Google Cloud Vision AI for content moderation and Firebase for backend functionality. Launched in 2021, the platform grew to over 1,000 users worldwide and was archived in 2023.
- Android (Java) – Native Android app developed in Java using Android Studio.
- Android Jetpack Components – Utilized ViewModel, LiveData, and Room Database for UI and data management.
- Glide – Image loading and caching for optimized performance.
- Firebase Firestore (NoSQL Database) – Stored user-uploaded images and metadata.
- Firebase Cloud Functions (Node.js) – Handled image processing and automated backend operations.
- Firebase Authentication – Enabled user login and secure authentication.
- Firebase Cloud Messaging (FCM) – Sent push notifications to users.
- Google Cloud Vision AI – Used to analyze and moderate uploaded images by detecting inappropriate or offensive content.
- Google Cloud Storage – Managed and stored user-uploaded images.
- Cloudflare CDN – Provided faster load times, reduced latency, and lower bandwidth costs by caching static content (such as images) at edge locations globally, ensuring users from different regions experienced minimal delay when accessing media.
- Performance Benefits: Improved response times by delivering cached images from the closest CDN node.
- Scalability: Handled high traffic loads efficiently by offloading requests from the primary storage.
- Security: Protected against DDoS attacks and provided secure data transmission via HTTPS.
To handle potential issues from user-uploaded large images:
- Designed a two-step pipeline: initial compression on device, followed by server-side resizing and WebP conversion using Cloud Functions.
- Reduced Cloud Storage usage, minimized bandwidth load, and improved delivery speed through CDN optimization.
- Developed an automated filtering system using Google Cloud Vision AI to detect and block explicit content.
- app/ – Main Android application source code (activities, fragments, resources).
- gradle/ – Build and dependency management configurations.
- .safedk/ – SafeDK integration files.
- .idea/ – Android Studio project settings.
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Clone the repository:
git clone https://github.com/danielkim-im/idolSnap.git
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Open the project in Android Studio.
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Ensure all dependencies are installed and build the project.
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Deploy the app to an emulator or physical Android device.
For more information, visit the project's website.
This project is licensed under the MIT License - see the LICENSE file for details.
Note: This project was archived in 2023 and is no longer actively maintained. Some dependencies or services may require updates for proper functionality.