MONAILabel
MONAI Label is an intelligent open source image labeling and learning tool.
Free, open-source period and cycle tracker. Offline. No account. No ads. Your data stays on your device.
HealthDart · HTMLGitHub @onepiece92OnlineOwner unconfirmed
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Free, open-source period and cycle tracker for iOS and Android. Works offline, no account, data stays on your device.
Taken from the repository README
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Read the full README ↗A free, open-source period and cycle tracker for iOS and Android. It works offline, needs no account, shows no ads, and keeps your data on your device.
Store title: Open Period & Cycle Tracker. Built by Brand Builder with Flutter. MIT licensed.
Track
Predict
Understand
Keep control
Full policy: https://brandbuilder.com.np/privacy-policy-for-open-period-cycle-tracker/ (also in PRIVACY_POLICY.md).
Does it work offline? Yes. Every feature runs on the device. Nothing requires a connection.
Do I need an account? No. Open the app and start logging.
What does it cost? Nothing. There is no subscription, premium tier, or in-app purchase.
Can I export my data? Yes. Profile → Backup exports a JSON file you can keep anywhere and restore later.
Where is the source code? Here: https://github.com/onepiece92/openPeriodTracker, under the MIT license.
Is it medical advice? No. The app is a tracking and information tool. Talk to a healthcare professional about anything that concerns you.
| Layer | Technology |
|---|---|
| Framework | Flutter 3.x, Dart 3.x |
| State management | provider |
| Local database | sqflite (SQLite) |
| Routing | go_router |
| Prediction | tflite_flutter with a small LSTM model trained by scripts/train_lstm_model.py |
| Typography | Google Fonts (Playfair Display, Outfit) |
Architecture is feature-first: lib/features/<feature>/ holds screens, lib/core/ holds models, providers, database and theme.
Prerequisites: Flutter SDK 3.x, Xcode for iOS or Android Studio for Android.
git clone https://github.com/onepiece92/openPeriodTracker.git
cd openPeriodTracker
flutter pub get
flutter run -d ios # iOS simulator
flutter run -d android # Android emulator
flutter run -d chrome # web
To regenerate the prediction model:
pip install tensorflow numpy
python scripts/train_lstm_model.py
Store metadata lives in fastlane/metadata/. The landing page lives in docs/ and is served by GitHub Pages.
See CONTRIBUTING.md. Contributions must keep the app offline-first and free of tracking. Security concerns: see SECURITY.md.
MIT. See LICENSE.