Senior Flutter Developer Required for Offline AI-Powered Camera & Image Processing Module

@ominfowave

Hello We are Ominfowave Software Services Pvt. Ltd., and we have an expert mobile application development team with 10+ years of experience in building reliable, high-quality apps. ? Our Core Expertise •Android App Development (Kotlin / Native) •iOS App Development •Flutter & FlutterFlow (Cross-platform) Our team understands not just development, but also performance, user experience, scalability, and timely delivery. ? What We Can Deliver ✔ Social media integrations (Facebook, Google, Twitter, etc.) ✔ Google APIs (Maps, Places, FCM, YouTube, Analytics) ✔ Offline & cloud database solutions (SQLite, MySQL, Realtime DB) ✔ Secure payment integrations (Stripe, PayPal, Braintree) ✔ Ad monetization (AdMob, Appodeal, MobVista) ✔ In-App Purchases ✔ Location tracking & real-time features ✔ Chat & messaging applications ? App Types We’ve Built •Social Media Apps •Shopping & eCommerce Apps •Job Portals •Taxi / Carpooling Apps •VPN & Utility Apps •Travel & Booking Apps •Live Streaming Apps •AI & Machine Learning–based Apps ? Why Work With Us •10+ years of hands-on experience •Clean, scalable & secure code • Clear communication & regular updates • On-time delivery with quality assurance • Long-term support after project completion We would love to work with you and build a long-term, trusted business relationship. Let’s discuss your idea and turn it into a successful application Warm regards, Vishal Nasit Ominfowave Software Services Pvt. Ltd.

@onkarkulkarni8

Hello, I'd love to help with your "Senior Flutter Developer Required for Offline AI-Powered Camera & Image Processing Module" project. I build fast, pixel-perfect static sites and landing pages in clean HTML5/CSS3 with Bootstrap or Tailwind — fully responsive across mobile, tablet, and desktop. For a fixed project involving android, dart, sqlite, image processing, opencv, documentation, flutter, computer vision, background removal, I translate Figma/PSD/XD designs into crisp, semantic markup that matches the design exactly. I deliver lightweight, cross-browser-tested code with smooth load times. Happy to discuss the details and timeline — when can we chat? Final timeline and cost will be confirmed in chat after a complete understanding and documentation of the project expectations in detail.

@mrresearcher99

Hello, I have 10 years of experience developing high-performance mobile applications with complex backend integrations and AI-powered features. Your offline photo processing pipeline is an ambitious project that requires careful architecture, native Android optimization, and efficient AI inference. I can develop the Flutter module with seamless native integration, focusing on responsive camera performance, offline-first architecture, multithreaded processing, SQLite/Drift synchronization, and maintainable code. My approach emphasizes modular design, secure coding practices, performance optimization, and efficient API integration where synchronization is required. I also have experience integrating AI capabilities into mobile applications, ensuring the solution is scalable, production-ready, and easy to maintain. I would be glad to discuss the processing pipeline, architecture, performance targets, and implementation strategy to deliver a reliable enterprise-grade solution. Best regards

@pinkeegupta

Hi I will be able to help you. Please message me so that we will have detail technical discussion. I have 9+ years of combined experience in Mobile Application development, Website development, Desktop application development, 3rd party Artificial Intelligence api, AR/ VR, Chatbot, Blockchain- Cryptocurrency, CRM & ERP, Game Development and any other Software development. I am having expertise in Native on Android Java, kotlin and IOS Swift, and For Hybrid Cross platform on Flutter Dart & React- Native, and for web and backend on react js and node js, Python Django. Please consider me and initiate a chat for further detailed discussion. Regards, Anju Logical Soft Tech Pvt Ltd, Indore(M.P)

@ixorawebmob

Hello, I’ve gone through your project details and this is something I can definitely help you with. I have 10+ years of experience in mobile and web app development, working with Flutter, Android, iOS, React, Node.js, and APIs. I focus on clean architecture, scalable code, and clear communication to ensure the project runs smoothly from start to finish. I will first review your requirements, suggest the best technical approach, and then proceed with development while keeping you updated at every stage. Here is my portfolio: https://www.freelancer.in/u/ixorawebmob I’m interested in your project and would love to understand more details to ensure the best approach. Could you clarify: What specific challenges do you anticipate in the offline AI processing features? 1. Do you need this for mobile, web, or both? 2. Do you already have UI/UX designs or should we create them? 3. Will there be any third-party API or payment gateway integration? 4. What is your expected timeline for completion? 5. Are there any reference apps or websites you like? Let’s discuss over chat! Regards, Arpit Jaiswal

@irfanui

I reviewed Senior Flutter Developer Required for Offline AI-Powered Camera & Image Processing Module as a robotics/vision engineering requirement with real hardware or simulation acceptance criteria. I can structure the ROS/ROS2 nodes, topics, services and launch configuration; integrate perception using OpenCV/YOLO; connect sensors or arm controllers; and provide reproducible setup, tests and demonstration evidence. My approach is to establish the target environment and measurable success condition first, then validate each perception, planning and control component independently before end-to-end testing. Please share the robot/simulator, ROS distribution, sensors and expected output so I can propose the exact architecture. Portfolio: https://www.freelancer.com/u/irfanui Regards, Mohammad 4th Dimension Partners

@TechizeBuilder

Dear Client, I read "Senior Flutter Developer Required for Offline AI-Powered Camera & Image Processing Module" carefully and understand you want a single Flutter codebase that runs smoothly on both Android and iOS. My hands-on experience with Android, SQLite, Flutter aligns directly with what you need. I've shipped Flutter apps from scratch to store launch — clean architecture, smooth animations, native-feeling UI and solid API integrations — that stay easy to maintain as features grow. A few quick questions to get us started: 1. Do you need Android, iOS, or both from day one? 2. Are UI designs ready, or should I design the screens as well? 3. Is there an existing backend/API, or should I build that too? Thanks & Regards, Deepak

@heenafullstacken

I would approach Senior Flutter Developer Required for Offline AI-Powered Camera & Image Processing Module as a measurable robotics system, with perception, communication, and control validated separately before the complete demonstration. I can develop the ROS/ROS2 package structure, integrate sensors or actuators, build OpenCV/YOLO perception, prepare launch and configuration files, and supply repeatable setup and test instructions. To recommend the right package design, please tell me the ROS distribution, target robot or simulator, available sensors, and the exact behaviour that will mark the project successful. Robotics profile: https://www.freelancer.in/u/heenafullstacken Kind regards, Heena | A Plus IT House

@ahsaans

Hi, I’ve carefully read the complete requirements for ID Mitra. I understand this is not a basic camera app, the main challenge is building a fast, fully offline AI photo-processing pipeline that can capture, validate, enhance, remove the background, and generate a professional ID photo in around one second. I can develop this using Flutter with native Android integration, Google ML Kit, MediaPipe, OpenCV, ONNX Runtime, MODNet, and Drift/SQLite. I’ll focus heavily on performance, memory optimization, isolates/multithreading, and keeping the UI responsive during AI processing. The complete workflow can work offline, including face detection, pose validation, auto-capture, image enhancement, background removal, passport framing, compression, and local queue management. Sync and uploads can run automatically when internet connectivity is available. I’ll provide clean modular source code, GitHub commits, documentation, testing, and performance optimization. Let’s connect in chat so I can discuss the architecture and show you relevant Flutter/AI work I’ve done.

@sajjadtaghvaeifr

Hello, I trust you're doing well. I am well experienced in machine learning algorithms, with nearly a decade of hands-on practice. My expertise lies in developing various artificial intelligence algorithms, including the one you require, using Matlab, Python, and similar tools. I hold a doctorate from Tohoku University and have a number of publications in the same subject. My portfolio, which showcases my past work, is available for your review. Your project piqued my interest, and I would be delighted to be part of it. Let's connect to discuss in detail. Warm regards. please check my portfolio link: https://www.freelancer.com/u/sajjadtaghvaeifr

@RajAbhisek

Offline AI camera modules with Flutter — this is exactly the kind of challenge we take on. We've worked with Google ML Kit, MediaPipe face landmarking, and OpenCV on Flutter/Android, and understand the constraints of running ONNX inference offline at sub-second latency on mid-range devices. For ID Mitra's photo capture module: the key is careful pipeline ordering (face detection → alignment → OpenCV enhancement → ONNX portrait enhancement → MODNet background removal), running heavy inference on Dart isolates to keep camera preview at 30–60 FPS, and batching WebP compression at the end. Memory-safe ONNX execution with proper tensor lifecycle management will be essential to avoid OOM on the MODNet background removal step. Quick question: have you validated the ONNX models for portrait enhancement and MODNet against your target mid-range Android spec, or do those need to be sourced and quantized as part of this scope?

@iimtpradeepdash

Getting sub-1s total processing and live 30–60fps preview with on-device AI, native side, and Flutter UI is the test here. ML Kit and MediaPipe/ONNX under one roof, all offline, is not for hobbyists. I’ve built Flutter modules for on-device face detection, liveness, alignment, custom OpenCV pipelines, and WebP output for a recent ID verification and onboarding SaaS in the education space, including SQLite sync and multi-model processing on mid-range devices. Approach: Flutter with native Android hooks for camera performance, ML Kit and MediaPipe for face tracking, ONNX/MediaPipe/EdgeTPU for model inference, OpenCV for enhancement, and MODNet ONNX for background. Isolates and native threads keep UI smooth, work queued for offline sync via Drift. Do you have pre-trained models for portrait enhancement, or do you want those sourced/tuned as well? Pradeep

@guptakishan805

Hi, I am a senior Flutter developer with hands-on experience in Computer Vision, OpenCV, MediaPipe, and ONNX Runtime for mobile. I can build your ID Mitra offline AI-powered camera module. My expertise covers: Flutter camera integration with live preview and overlay guides, face detection and validation using MediaPipe Face Landmarker and Google ML Kit, AI-powered portrait enhancement using ONNX Runtime with MODNet for background removal, image processing pipeline with OpenCV for auto-crop, perspective correction, brightness/contrast adjustment, white balance, CLAHE enhancement, and sharpening, passport photo validation with face position, head size, and margin verification, offline-first architecture with SQLite/Drift for local storage, background sync with upload queue and automatic retry, WebP compression targeting 100-150 KB with high visual quality, and performance optimization under 1 second total processing time. I have previously worked on document scanning and face recognition applications. Clean architecture, modular codebase, unit tests, and GitHub commits throughout development included.

@tyagi5011

As an experienced Flutter developer with a specialisation in Computer Vision and AI model deployment on mobile, I believe that I am the best fit for your project. With over 6 years in the industry, I've successfully delivered a diverse range of Android applications including Video Calling Apps and Doctor Consultation Apps - projects that necessarily involve advanced camera functionalities. Equally essential to this project is my competence in, and work with OpenCV, Google ML Kit, MediaPipe and ONNX Runtime - all skills mentioned as crucial requirements for this project. Furthermore, my expertise extends not just to crafting the desired functionality but also ensuring the underlying performance benchmarks are met. My prior experience with enhancing app performance for Flutter applications makes me particularly adept at optimizing speed and managing battery usage. It's worth noting that offline-first applications are an area where I hold significant experience too. Delicately managing local storage, queue management, and background synchronization without relying excessively on the internet aligns with my skill set. To summarize, my proficiencies in designing and optimizing high-quality digital products make me the right choice for your image-processing module. Rather than just delivering the code, I will take up end-to-end responsibility ensuring the crafted system performs as expected in real-world contexts. Let's make ID Mitra the ideal ID card photo capture solution!

@ashinnd84

Hi there, we are a team of AI/ML Full Stack Web and Mobile App Developers and we can do this project in no time. Thanks Ashish Kumar.

@WOFZahid

Hello, Your project aligns well with my experience in Flutter, AI integration, computer vision, and offline-first application development. Building a production-grade offline ID photo pipeline requires careful optimization across camera capture, ML inference, image processing, and background synchronization rather than simply integrating libraries. I can develop a modular Flutter solution integrating Google ML Kit, MediaPipe Face Landmarker, OpenCV, ONNX Runtime Mobile, MODNet, SQLite/Drift, and WorkManager to deliver automatic face detection, alignment, enhancement, background removal, passport validation, WebP compression, and reliable offline queue synchronization. I focus on clean architecture, native Android performance optimization, isolates for heavy processing, memory-efficient image pipelines, and responsive UI while targeting your required processing times on mid-range Android devices. You'll receive complete source code, GitHub-based development with regular commits, documentation, unit tests, and a production-ready implementation. I'm available to discuss the AI models, device targets, and development milestones before we begin.

@farhan2quasimi

Hi, I've read the full project specification. This is a well-architected brief — the processing pipeline (ML Kit → MediaPipe → OpenCV → ONNX/MODNet → WebP compression) is technically demanding, and the 1-second total processing target on mid-range Android is achievable but requires careful isolate and memory management in Flutter. We have a mobile team with hands-on experience in: Flutter camera integration with live face tracking and auto-capture triggers Google ML Kit face detection with quality scoring OpenCV image processing via FFI/platform channels in Flutter ONNX Runtime Mobile for on-device AI inference Offline-first SQLite/Drift architecture with background sync The key technical challenge here is keeping the UI thread responsive while running the OpenCV + ONNX pipeline concurrently — we'd handle this using Dart isolates for processing and platform channels for native OpenCV calls. Milestones: Week 1–2: Camera module, ML Kit face detection, MediaPipe alignment Week 3–4: OpenCV processing pipeline, ONNX portrait enhancement Week 5: MODNet background removal, passport framing validation, WebP compression Week 6: SQLite/Drift offline storage, background sync, testing + optimization For the full scope as specified, a realistic budget is ₹75,000–₹1,00,000 INR. Happy to discuss phased milestones. Can we schedule a call to discuss the ONNX model you're planning to use for portrait enhancement? Farhan Technical PM & IT Strategist

@ViranderK

Hi, I came across your requirement and found it very interesting. I have **11+ years of mobile development experience** and **7+ years with Flutter**, building high-performance mobile applications, including AI-powered solutions, OCR, Google ML Kit integrations, offline-first apps, and camera-based workflows. I've also worked on Flutter performance optimization, native Android integrations, background processing, and clean modular architectures. Your vision for **ID Mitra** is well-defined, and I understand the importance of delivering a fast, offline AI pipeline while maintaining a responsive UI. I can implement the complete workflow using **Flutter, Google ML Kit, MediaPipe, OpenCV, ONNX Runtime, SQLite/Drift, WorkManager, and isolates** to achieve near real-time image processing. The solution will be modular, production-ready, well-documented, and optimized for memory, battery, and performance. **Estimated Timeline:** 8–10 weeks **Estimated Cost:** ₹85,000 (MVP). After reviewing the AI models, existing architecture, and performance benchmarks, I'll provide a detailed milestone plan for the complete implementation. A couple of questions: 1. Are the ONNX models (MODNet & Portrait Enhancement) already finalized? 2. Is there an existing Flutter project, or will this module be developed from scratch? Looking forward to discussing the project. Best, **Virander**

@somendersingh96

Hello, I can develop your AI-powered offline photo capture and enhancement module for ID Mitra, delivering a production-ready Flutter solution optimized for speed, accuracy, and complete offline operation. My approach includes: * Building a high-performance Flutter camera module with Google ML Kit, MediaPipe, OpenCV, ONNX Runtime, and MODNet. * Implementing automatic face detection, alignment, quality validation, passport framing, portrait enhancement, background removal, and WebP compression. * Developing an offline-first architecture using SQLite/Drift, background upload queues, WorkManager, and automatic synchronization. * Optimizing performance with isolates, native Android integration, memory management, and AI inference to achieve near 1-second processing on supported devices. I have experience building Flutter applications, AI-powered image processing systems, OpenCV pipelines, ONNX Runtime integrations, offline-first mobile apps, and performance-optimized Android solutions. Ready to start immediately and deliver clean, modular, well-documented code with continuous GitHub commits. Best regards, Somender Singh