Smart Photo Selector App -- 2

@leadconcept

Hi, We can build an on-device photo app that clusters faces reliably, places uncertain matches into an Unsorted bucket, and lets you pick images individually, by date range, or by geolocation, including combined filters. The app will prioritise privacy, use proven on-device CV (Apple Vision, Google ML Kit, or OpenCV), provide a simple correction UI, and hand selections to the native share sheet. Questions, 1. Which platform first, iOS, Android, or cross-platform? 2. Typical library size to optimise performance and caching? 3. Any hard privacy rules beyond local processing? Our team of computer vision engineers and mobile developers will deliver the app, source code, and test instructions. Chat with us to confirm scope and timeline, the current bid amount is a placeholder to submit the proposal. Regards Yasir LEADconcept PS: Let me know, if you want to see our team past work to determine our skills/expertise or past customer's references.

@badarmadni927

As an experienced mobile app developer with a specialization in both Flutter and React Native, I am confident that I can turn your project vision into reality. Specifically, I am well-versed in leveraging powerful technologies like Vision/Core ML, Google ML Kit, and OpenCV to implement face detection and efficient photo filtering, both of which are essential for your Smart Photo Selector App. My expertise goes beyond just implementing features; it extends to creating user-friendly apps with top-notch UI/UX designs. And since accurate and efficient photo clustering is paramount to your project, I appreciate the inclusion of an easy way to correct any mistakes the algorithm may make. My skills in state management using Hooks and Bloc will ensure a smooth and error-free user experience.

@technologybeach

With a packed toolbox and a diverse set of skills, I'm the perfect fit for building your Smart Photo Selector App. Not only do I possess extensive experience in Mobile App Development and a deep-rooted knowledge of face detection algorithms (you mentioned Apple’s Vision/Core ML, Google ML Kit, OpenCV or another proven face-clustering library), but I also understand the importance of accuracy in this context. Hence, my proficiency with analyzing and clustering faces will not only ensure precision but provide an easy way for you to correct any false identification. One thing that sets me apart is my approach to designing user-friendly interfaces. As you laid it out, I see how important surfacing filters like individual selection, date range, and geolocation are to navigate your photo library intuitively. My design capabilities extend to an excellent user experience that conveniently merges these filters - making sure they are central in the app's interface keeping your existing mental model undisturbed. Finally, something I consider a unique advantage is my capacity to offer you an end-to-end solution from design to deployment. This means not only delivering the functional mobile app coded in your preferred tech stack but also empowering you with the knowledge necessary to compile and test it on your own device. Let's turn your vision into reality!

@mrresearcher99

Hi there, I’ve reviewed your Flutter app requirements and would love to help. With 5+ years of experience in cross-platform development, I specialise in clean UI, smooth performance, and robust API integration. I’ll begin with clear planning, share regular progress updates, and ensure the app is fully tested before launch. Let’s connect to discuss your vision — I’m ready to get started! Best, Bhargav Flutter Developer | Android & iOS Expert

@OutsourceMan

⭐⭐⭐⭐⭐ Thank you for sharing your project requirements. CnELIndia, in collaboration with Raman Ladhani, can help deliver this app end-to-end with precision and efficiency. We propose leveraging Apple’s Vision and Core ML for iOS and Google ML Kit for Android to implement accurate on-device face clustering, minimizing false positives and automatically handling uncertain matches via an “Unsorted” bucket. Our team will build an intuitive interface that prominently supports selection by individual images, date ranges, and geolocation, allowing combinations seamlessly. The final workflow will integrate the system share sheet for easy forwarding across all channels. CnELIndia will manage the full mobile app development, cross-platform testing, and source code delivery, while Raman Ladhani provides expertise in face recognition, OpenCV optimization, and performance tuning, ensuring reliable, privacy-preserving results. Together, we guarantee a high-quality, fully functional app that meets your expectations efficiently.

@vishal1145

Your face-clustering accuracy will drop below 70% if you rely solely on Apple Vision without implementing a secondary confidence threshold and manual review queue. I've seen this exact pattern fail in production when users have 10K+ photos - the algorithm starts grouping siblings or colleagues as the same person, and there's no easy way to split clusters after the fact. Before architecting the solution, I need clarity on two things: What's the average photo library size you're targeting (5K, 20K, 50K images)? And do you need this to work offline, or can the initial clustering happen with cloud assistance to speed up processing on older devices? Here's the architectural approach: - FACE RECOGNITION + OPENCV: Implement a two-pass system using Apple Vision for initial detection, then OpenCV's face descriptor comparison with a 0.6 similarity threshold to reduce false positives by 40%. Unsure matches (0.4-0.6 range) automatically route to your manual review bucket. - CORE ML OPTIMIZATION: Batch process images in groups of 50 using background threads to prevent UI freezing. On an iPhone 12 with 10K photos, this completes clustering in under 3 minutes versus 15+ minutes with sequential processing. - GEOLOCATION + DATE FILTERING: Build a compound query system that indexes photos by EXIF metadata on first scan, then uses SQLite for sub-100ms filter responses when you're combining location radius + date range selections. - CROSS-PLATFORM CONSIDERATION: If you need both iOS and Android, I'll use Flutter with platform channels to access native Vision/ML Kit APIs. Pure native (Swift + Kotlin) gives 30% better performance but doubles development time. I've built similar face-clustering systems for 2 photo management apps that processed 500K+ images across 5K users. The tricky part isn't the detection - it's handling edge cases like masked faces, profile shots, and preventing memory crashes during bulk operations. Let's schedule a 15-minute call to walk through your photo library structure and discuss whether you need real-time clustering or batch processing.

@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 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 , java spring boot and php CodeIgniter mvc. Please consider me and initiate a chat for further detailed discussion. Regards, Anju

@rbtech1984

Hello There!!! ★★★★ ( Smart Photo Selector App ) ★★★★ I understand you need a mobile app that scans the camera roll, accurately clusters faces of the same person, and lets you select images to share individually, by date range, or geolocation. The focus is on privacy, on-device processing, minimal false positives, and an intuitive interface with flexible filters. ⚜ Automatic face clustering with minimal errors and “Unsorted” bucket for uncertain photos ⚜ Filters to select photos individually, by date range, or geolocation ⚜ Bulk or single photo selection workflow ⚜ Integration with system share sheet for easy sharing ⚜ On-device processing using Vision/Core ML, ML Kit, OpenCV, or similar ⚜ Cross-platform support for iOS and/or Android ⚜ Full source code with setup instructions for compiling and testing With 9+ years experience in mobile apps, including face detection and efficient media filtering, I can deliver a smooth, private, and reliable photo selection experience. I’ll ensure the interface is intuitive and the clustering algorithm accurate. Looking forward to building this smart selector app with you! Warm Regards, Farhin B.

@devbaloni1983

Hello, I am an expert with 15+ years of experience in the technical world, delivering simple to complex websites, e-commerce platforms, membership systems, and custom portals. I ensure clear communication, continued support after delivery, and 100% client satisfaction. I specialize in Mobile App Development, creating fast, user-friendly, and feature-rich apps for both Android and iOS. My focus is on modern UI/UX, API integration, real-time features, and cross-platform compatibility, ensuring your app is scalable and future-ready. If you are looking for a dedicated Mobile App Developer who delivers quality, innovation, and timely results, I’d be happy to bring your project to life. Best regards,

@trm66614

Hi there,Good evening I am Talha. I have read you project details i saw you need help with Face Recognition, iPhone, C# Programming, OpenCV, Android App Development, iOS Development, Android and Mobile App Development I am writing to propose an innovative approach to tackle your project. Our proposal centers on delivering creative and effective solutions that will set your project apart. We will present fresh, out-of-the-box ideas that align with your project's objectives, demonstrating how we can achieve remarkable results. Please note that the initial bid is an estimate, and the final quote will be provided after a thorough discussion of the project requirements or upon reviewing any detailed documentation you can share. Could you please share any available detailed documentation? I'm also open to further discussions to explore specific aspects of the project. Thanks Regards. Talha Ramzan

@Riasatali78

I’ve implemented on-device face detection and photo-library processing with high accuracy and privacy-first design. I can deliver a clean MVP with reliable clustering, flexible filters, and a smooth native share workflow.

@mobiwebsolutions

✋ Hi There!!! ✋ The Goal of the project:- Build a Smart Photo Selector app that accurately clusters faces, provides advanced filtering options, and enables seamless sharing of selected images. I have carefully read and understood your project description and can develop a mobile app that scans the camera roll, clusters faces with minimal false positives, and offers intuitive filters for individual selection, date ranges, and geolocation. I am the best fit for this project because I have hands-on experience implementing on-device face recognition and efficient photo management workflows. I can provide: 1. Automatic face clustering with an easy correction interface. 2. Filters for selecting photos individually, by date range, or geolocation. 3. Integration with the system share sheet for smooth image sharing. I offer services including UI design, database management, testing, and full source code delivery. I have 9+ years experience as a full stack developer and have completed similar photo recognition and mobile gallery projects. Looking forward to chat with you for make a deal Best Regards Elisha Mariam!

@arbu1499

I understand you need an on-device photo app that scans the camera roll, clusters the same person across images with high accuracy (and an “Unsorted” fallback for low-confidence matches), then lets you select photos individually, by date range, or by geolocation before sending them through the native share sheet. I’d build this natively in Swift using Apple Vision + Core ML for private, on-device face embeddings and clustering, with a clean correction workflow and efficient photo indexing for smooth performance even on large libraries. Full source code, build steps, and clear architecture handoff will be included. Looking forward for your positive response in the chatbox. Best Regards, Arbaz T

@Shaiwan

Hello!!! I HAVE ALREADY WORKED ON SIMILAR TYPE OF PROJECT OPEN CHAT WINDOW I WILL SHARE MY WORK Do you want the first version focused on iOS using Vision/Core ML or Android with ML Kit? Should face clustering run fully on device only, with no cloud processing at all? What I offer: ⭐ Accurate on device face detection and clustering using Vision, ML Kit or OpenCV ⭐ Smart grouping with Unsorted bucket for low confidence matches ⭐ Advanced filtering by date range, geolocation and manual selection ⭐ Smooth bulk select and intuitive gallery style interface ⭐ Native share sheet integration for all installed apps ⭐ Clean source code with setup guide for local compilation I have 7+ years of experience in mobile development and computer vision based applications. My approach: choose the most reliable on device ML framework, implement clustering with confidence scoring, then optimize performance for large photo libraries. Let’s open a chat to finalize platform choice and timeline. Best Regards, Shaiwan Sheikh

@kishanbwts

Your app’s main challenge is accurate face grouping combined with flexible, intuitive filtering. In a previous project, I built a photo sorting tool that clustered faces using Apple Vision on-device, keeping all data private and minimizing false matches by creating an “Unsorted” bucket for unclear cases—just like you want. For filters, I layered date and geolocation selectors that users could combine smoothly, which helped people manage large libraries quickly. I suggest using Apple’s Vision framework if targeting iOS, as it’s reliable and optimized for privacy. Would you prefer a native iOS app for best performance, or cross-platform to cover Android as well? Also, do you want continuous clustering updates when new photos arrive, or just a one-time scan? I can deliver a clean UI highlighting those three filters clearly and a seamless share sheet integration for all sharing options. Ready to start building this smart, user-friendly photo selector for you.

@MIndlabsAi6

Hello, I am Vishal Maharaj, a seasoned professional with 20 years of expertise in C# Programming, iOS Development, Android App Development, Android, OpenCV, iPhone, and Mobile App Development. I have carefully reviewed your project requirements for the Smart Photo Selector App. To achieve the desired outcome, I propose utilizing a combination of Apple's Vision/Core ML and OpenCV for accurate face clustering and photo filtering. The app will seamlessly analyze and group photos based on individuals, allowing for easy selection through filters by date range, geolocation, or individual choice. The final selection can then be shared through various channels using the standard share sheet. I am confident in delivering a fully functional mobile app that meets all your requirements. Please initiate a chat to discuss further details. Cheers, Vishal Maharaj

@SalinaSof30

HELLO, I HAVE SUCCESSFULLY DELIVERED AI-BASED PHOTO & ML FEATURES & CAN PRESENT SIMILAR WORK With 6 years of mobile development experience, including on-device ML and media-heavy applications, I can build your Smart Photo Selector with strong accuracy and smooth performance. Since privacy is critical, I would prioritize fully on-device processing using Apple Vision/Core ML (for iOS) or Google ML Kit (for Android), ensuring no photos leave the user’s device. The app will scan the camera roll, extract facial embeddings, and cluster images using similarity thresholds. When confidence is low, photos will automatically fall into an “Unsorted” bucket to avoid false positives. I’ll implement a clean correction workflow so users can manually reassign images between clusters. Filtering will be prominently designed: • Individual selection • Date range filtering (native metadata-based queries) • Geolocation filtering using EXIF coordinates These filters can be combined seamlessly for bulk selection. Once finalized, the app will trigger the native system share sheet (Messages, WhatsApp, AirDrop, email, etc.). The codebase will be modular, documented, and optimized for handling large libraries efficiently. I can deliver a functional first version on one major platform quickly, with clean source code and setup instructions for local testing. Confident this can be built cleanly and reliably. Thanks

@billybryan98

Hello, I hope you are doing well. I am a mobile developer specialized in on-device ML and privacy-first photo apps. My background spans iOS and Android, with hands-on work using Vision/Core ML, ML Kit, and OpenCV to build fast, reliable face clustering that keeps user data on the device. I design robust UIs that surface three core filters, by date, by geolocation, and by individual photos, so you can curate selections exactly how you think about your library. In previous projects I built end-to-end photo libraries with consent-based face grouping, an Unsorted bucket for uncertain results, and straightforward correction workflows to improve accuracy over time. I’ve delivered modular components that plug into native platforms and provide smooth share-sheet integration for exporting selected images via Messages, WhatsApp, AirDrop, Email, etc. I can handle this project end-to-end using my expertise in mobile development and on-device ML. I’ll implement accurate clustering with easy manual overrides and a clean, responsive UI that matches your workflow. I guarantee a solid, production-ready result. Best regards, Billy Bryan

@sadaqatzia

Hey , I just finished reading the job description and I see you're looking for someone experienced in C# Programming, Face Recognition, iPhone, OpenCV, Android App Development, Android, Mobile App Development and iOS Development. This is exactly what I specialize in. I’ve worked on various AI projects, including NLP, Multi-Agent systems, Computer vision, AI Automation, Agentic AI, Fine-Tuning, LLMs, and Predictive Analytics. My solutions have helped businesses automate workflows, reduce errors, and make smarter decisions using data-driven models. A few quick questions before we proceed: 1- Are these all the requirements, or do you have a detailed scope? 2- Are we starting from scratc,h or is there existing work to build upon? Why Choose Me? 1- Successfully delivered 100+ AI projects for global clients 2- My AI systems have improved business efficiency by up to 50% 3- Deep expertise in OpenAI, Python, TensorFlow, NLP, and automation Let’s connect and discuss how I can bring smart AI solutions to your project. Regards, Sadaqat Zia