Enhance Application with Experienced Flutter Developer for Offline AI-Powered Camera & Image Processing Module
Publicada el 2026-07-21
Descripción de la oferta
We are developing an enterprise-grade SaaS platform called ID Mitra, an ID Card and Attendance Management solution used by schools, colleges, universities, corporate organizations, and government institutions. As part of our platform, we are building an advanced AI-powered offline photo capture and enhancement system for Android devices. The objective is to enable users to capture professional-quality ID card photographs directly from a mobile device without requiring an internet connection. This is not a simple camera application. We are looking for an experienced developer who has worked with Computer Vision, AI inference, image processing, and Flutter performance optimization. Project Objective Develop a high-performance Android module that automatically captures, validates, enhances, and processes ID card photographs completely offline. The user should simply point the camera at the student, and the application should automatically produce a professional passport-style photograph within approximately one second. Core Features Camera Module Flutter Camera Integration Live Camera Preview Camera Overlay Guide Auto Focus Auto Exposure Flash Control Auto Capture when conditions are satisfied Continuous Face Tracking Face Detection (Google ML Kit) Single Face Detection Eye Open Detection Smile Detection Face Angle Detection Face Distance Validation Face Quality Score Live Face Tracking Face Alignment (MediaPipe) Face Landmark Detection Face Rotation Face Alignment Face Centering Facial Pose Estimation Landmark Validation Image Processing (OpenCV) Auto Crop Face Centering Perspective Correction Brightness Adjustment Contrast Adjustment White Balance Gamma Correction CLAHE Enhancement Sharpening Noise Reduction Blur Detection Image Quality Analysis Automatic Resize Portrait Enhancement (ONNX Runtime) Natural Portrait Enhancement Face Detail Improvement Skin Tone Balancing Lighting Correction Facial Detail Restoration Color Enhancement Note: We do not want beauty filters or unrealistic face modifications. Background Processing Background Removal (MODNet) Pure White Background Generation Hair Edge Refinement Background Quality Validation Passport Photo Validation Face Position Verification Head Size Verification Top Margin Validation Chin Position Validation Automatic Passport Framing Professional ID Photo Output Compression Convert to WebP Target file size between 100 KB and 150 KB Maintain high visual quality Offline Functionality The complete image processing pipeline must work without an internet connection. Offline features include: Camera AI Processing Image Enhancement Background Removal Compression Local Storage Queue Management Only synchronization should require internet access. Background Synchronization SQLite / Drift Database Upload Queue Automatic Retry Background Sync Upload Progress Error Recovery Performance Requirements The application should meet the following targets on modern mid-range Android devices: Camera Preview: 30–60 FPS Face Detection: under 50 ms Face Alignment: under 40 ms OpenCV Processing: under 150 ms Portrait Enhancement: under 250 ms Background Removal: under 350 ms Total Processing Time: approximately 1 second The UI must remain responsive throughout processing. Required Technologies Flutter (latest stable) Dart Google ML Kit MediaPipe Face Landmarker OpenCV ONNX Runtime Mobile MODNet (ONNX) SQLite / Drift flutter_image_compress Background Services / WorkManager Git GitHub Developer Requirements We are looking for someone who has experience with: Flutter application development Android native integration Computer Vision OpenCV ONNX Runtime AI model deployment on mobile MediaPipe Performance optimization Offline-first mobile applications Memory optimization Battery optimization Multithreading and isolates Experience building AI-powered camera or image-processing applications is highly preferred. Deliverables The selected developer will be responsible for: Complete source code Clean architecture Modular codebase Documentation Unit tests Performance optimization Production-ready implementation GitHub commits throughout development Preferred Candidate We prefer developers who have previously worked on: Passport photo applications Document scanning applications Face recognition systems AI camera applications OCR applications Image enhancement applications Mobile computer vision projects
Skills
Fuente original: freelancer