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# 🌟 Contributing to PictoPy
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# Contributing to PictoPy
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Hi there! Thank you for considering contributing to **PictoPy** – we’re excited to collaborate with you. Whether you're fixing a bug, improving documentation, or suggesting a new feature — you're welcome here!
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NOTE: Please do not open a PR for the issue which is not yet reviewed and labelled by the maintainer. Wait for the maintainer to give a green light.
PictoPy is an advanced desktop gallery application that combines the power of Tauri, React, and Rust for the frontend with a Python backend for sophisticated image analysis and management.
1. First, join the **[Discord Server](https://discord.gg/hjUhu33uAn) (Go to Projects->PictoPy)** to chat with everyone.
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2. For detailed setup instructions, coding guidelines, and the contribution process, please check out our [CONTRIBUTING.md](./CONTRIBUTING.md) file.
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# PictoPy
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# Architecture
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**PictoPy is an open-source, privacy-first AI photo management application built for the desktop - featuring on-device face recognition, object detection, and smart search, with zero data leaving your machine.**
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### Frontend
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PictoPy brings the intelligence of modern AI photo management to your local machine, without the privacy trade-offs of cloud-based alternatives. Built as a fully offline desktop application with Rust, React, and Python, PictoPy automatically groups faces across your library, tags photos with detected objects, and lets you search your pictures with simple words - all powered by state-of-the-art on-device models, without an internet connection or a subscription.
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-**Tauri**: Enables building the desktop application
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-**React**: Used for creating the user interface
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-**Rust**: Powers the backend, which the frontend communicates with through Tauri's API
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Find out more at [https://pictopy.aossie.org/](https://pictopy.aossie.org/).
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### Backend (Python)
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##Features
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-**FastAPI**: Serves as the API framework
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-**SQLite**: Database for storing metadata and embeddings
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-**YOLO**: Used for object detection
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-**FaceNet**: Generates face embeddings
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-**ONNX Runtime**: Runs the models efficiently
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-**DBSCAN**: Performs clustering for face embeddings
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**AI-powered**
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* Smart tagging based on detected faces and objects
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* Advanced image analysis with object detection and facial recognition
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* Smart search and retrieval
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### Backend (Rust via Tauri)
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**Gallery management**
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* Album management with traditional gallery features
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* Cross-platform compatibility
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Handles file system operations and provides a secure bridge between the frontend and local system.
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**Privacy & performance**
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* Privacy-focused design with fully offline functionality
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* Efficient data handling and parallel processing
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## Features
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## Demonstration
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- Smart tagging of photos based on detected objects, faces, and their recognition
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- Traditional gallery features of album management
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- Advanced image analysis with object detection and facial recognition
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- Privacy-focused design with offline functionality
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PictoPy uses several SQLite databases to manage various aspects of the application. This document provides an overview of each database, its structure, and its primary operations.
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