Smart Photo Selector App -- 2

@KESHAVINFOTECH

Hi There, 1.I want an app that scans the phone’s camera roll, recognises the same p... ==> We got the idea for your app. Scanning the camera roll to group photos by people is a great concept. We have done similar projects in the past that involved managing large photo libraries and on-device machine learning. One of the apps we built had a smart feature that would not only group faces but also automatically suggest the single best photo from a burst of similar shots, helping users clean up duplicates easily. We understand the selection process is very important. We will design the interface so that filtering by date range and location is simple and clear. You will be able to combine these filters to find exactly the photos you need. ## Queries : 1. When the app incorrectly creates two different groups for the same person, what would be the ideal user flow for merging these two groups into one? ## Initial Project Structure : - Main Gallery (with face groups) - Group Detail (viewing photos of one person) - Photo Viewer and Selector - Filter Options - Unsorted Photos - Settings We use advanced AI tools (Cursor, Claude, ChatGPT) to speed up coding and reduce manual work hours. We pass these time-savings to you, providing a high-quality app at a very competitive price. Waiting for your reply. :-) Regards, Ghanu & Samir. KESHAV INFOTECH

@AwaisChaudhry

Hello, I understand you want a fast, private, on-device photo tool that groups faces across your camera roll and lets you pick exact pictures to share. My plan is to build a responsive app (native or cross-platform) that uses a robust face clustering engine (Vision/Core ML on iOS, ML Kit or OpenCV elsewhere) to form accurate groups; uncertain results go to an Unsorted bucket for easy manual correction. You’ll see three prominent filters, by date, by geolocation, and by individual, with options to combine them, and a seamless path from selection to the system share sheet. I’ll deliver clear source code and setup steps so you can compile and test on your device. Which platforms should we target first (iOS-only or also Android)? Do you want on-device processing exclusively, or is a cloud-assisted approach acceptable if it preserves privacy and performance? Any privacy policy or data retention rules we should follow for photo processing? Do you have a preferred face clustering library, or is it okay to use Vision/Core ML or ML Kit if it’s proven on-device and private? How should the Unsorted bucket be surfaced and edited within the UI? Should geolocation be based on photo EXIF data, or do you want a map-based view for filtering? How should multiple faces in a single photo be represented in clusters (one face per photo, or multiple faces grouped if same person appears)? Do you want support for additional share targets beyond the system share sheet (e.g., in-app messaging i

@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.

@leadconcept

Greetings, I understand you are looking for a mobile app that scans a device’s camera roll, automatically clusters faces by individual, and allows selective sharing through standard channels, while giving full control over date, geolocation, and individual photo selection. Before we proceed, I would like to clarify a few things. 1, Do you prefer a native solution (iOS/Android) or a cross-platform framework such as Flutter or React Native. 2, Approximately how many photos do you expect the app to handle, as this will affect performance and on-device processing choices. Our team includes mobile developers experienced with on-device ML, face detection, clustering, and secure photo handling, using Apple Vision/Core ML, Google ML Kit, OpenCV, and other efficient libraries. We focus on privacy, speed, and an intuitive interface that lets users easily filter, correct, and share photos. Let us connect to discuss your requirements, timeline, and expected outcomes. The current bid amount is a placeholder to start the conversation. 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.

@corpmember29

Hello, {{{ I HAVE CREATED SIMILAR APPS BEFORE AND I CAN SHOW YOU }}} I can build this app with a strong focus on on-device privacy, accuracy, and a clean selection workflow. The core approach would be: • Use native on-device face detection + embeddings (Apple Vision/Core ML on iOS or ML Kit on Android) to cluster faces reliably without uploading photos • Implement confidence thresholds so uncertain matches are automatically placed in an “Unsorted” bucket for manual correction • Store face clusters locally and allow users to reassign photos between groups with simple gestures • Build a fast photo selection layer with three combinable filters: individual selection, date range, and geolocation (using photo metadata indexing for performance) • Final selection opens the system share sheet (Messages, WhatsApp, AirDrop, Mail, etc.) with zero data duplication I have 10+ years of experience in mobile development, computer vision integrations, and privacy-first photo processing workflows. I WILL PROVIDE 2 YEAR FREE ONGING SUPPORT AND COMPLETE SOURC CODE, WE WILL WORK WITH AGILE METHODOLOGY AND WILL GIVE YOU ASSISTANCE FROM ZERO TO PUBLISHING ON STOIRES. I eagerly await your positive response. Thanks.

@Julian29

Hello, HAVE HANDS-ON EXPERIENCE WITH SUCH PROJECT. I bring 15+ years of proven experience in mobile development and computer vision, and I confidently understand your requirements. The goal is to build a privacy-focused smart photo selector that accurately clusters faces on-device while giving users intuitive control through date and geolocation filters. Core features: -->> On-device face detection and clustering (Vision/Core ML or ML Kit) -->> “Unsorted” bucket for low-confidence matches with manual correction -->> Multi-filter selection: individual, date range, geolocation (combinable) -->> Seamless system share sheet integration -->> Clean, well-documented source code with setup instructions My approach emphasizes clean architecture, efficient on-device processing, and modular design for scalability. I have some queries regarding your preferred platform (iOS first or cross-platform) before proceeding. I would begin with a clustering accuracy prototype, followed by UI/UX flow design and iterative development through final testing. I am confident I can successfully implement this project from start-to-finish and deliver a fast, accurate, and privacy-respecting photo selection app. Thanks & regards, Julian

@planDapps

ON DEVICE INTELLIGENCE: PRIVACY FIRST FACE CLUSTERING & SMART FILTERS Hi, Efficient photo management requires a robust local processing engine that respects user privacy. At Plan D Studios, we bring 12+ years of experience in mobile app development and custom software, specializing in on device machine learning and high performance app design. Our Technical Approach: Preferred Stack: We recommend a native first approach using Apple’s Vision framework and Google ML Kit for high speed, local Face Recognition without cloud latency. Unified Filtering Engine: We will build a high performance indexer that allows users to intersect clusters with date ranges and GPS coordinates. Accuracy & Logic: Following your "Unsorted" bucket requirement, we’ll implement confidence thresholds to minimize false positives, ensuring only verified matches populate the primary clusters. Seamless Sharing: Full integration with the OS share sheet for immediate distribution across any platform. We do NOT outsource. Our in house team handles the entire lifecycle, from metadata indexing to the final iOS Development or Android app development build. We have a strong background in C# Programming and OpenCV for specialized image processing tasks. Do you plan to support continuous background indexing to keep the gallery updated as the user takes new photos? Let’s discuss your library architecture message us to start the technical audit. Regards, Haider

@OutsourceMan

⭐⭐⭐⭐⭐ Dear Valuable Client, CnELIndia, together with Raman Ladhani, can help you deliver a highly accurate, user-friendly mobile app that meets all your requirements. We propose using Apple’s Vision/Core ML for iOS and Google ML Kit for Android to perform on-device face clustering while preserving privacy. Our approach ensures minimal false positives by placing uncertain matches in an “Unsorted” bucket for manual review. We will implement intuitive filters for individual, date-range, and geolocation selection, allowing combined queries. Finally, the selected images will be shared via the native share sheet. CnELIndia will handle architecture, cross-platform compatibility, and performance optimization, while Raman Ladhani will provide hands-on expertise in face recognition, OpenCV integration, and mobile UX, ensuring a reliable, scalable, and maintainable solution. We can also provide full source code with setup instructions for seamless testing.

@technologybeach

As an experienced Full Stack Developer and Software Engineer, I have honed my skills in Website Development, Mobile App Engineering (both Native and Hybrid), and Creative Design, making me an ideal candidate for your Smart Photo Selector App project. My career has been built on the ability to deliver scalable, high-performing digital products like the one you seek. I am comfortable with a range of tech stacks, and this includes profound knowledge of Apple's Vision/Core ML and Google ML Kit which aligns well with your preference for a proven face-clustering library that balances reliable processing with privacy protection. Moreover, my proficiency in mobile app development for both Android and iOS ensures that your deliverables will be met to the highest standards on at least one major platform. Beyond the technical competence, my strength in problem-solving, time management, and team leadership greatly complement the agile management approach that drives your project. I'm excited about potential synergies in our work methodologies and believe our collaboration would drive an intuitive user experience to promptly forward selected pictures, using preferred installed channels via the system share sheet while providing an "Unsorted" option for photos where face-grouping algorithm may have uncertainty. Let's transform your groundbreaking idea into an effective reality.

@caroldata

I can develop your E-commerce Web and APP as per your need. * I am familiar with android/IOS applications for both native and hybrid apps. I have 6 years of experience on mobile applications ( Android +iPhone/ iPad ) and App admin with development web services where admin can manage the app from the back end, I have developed the TAXI apps, google map, Event App, Job Portal App, Restaurant App, Dating App, Social chat with video calling and other apps with clients need I will never disappoint you in terms of quality of work, deadline, and communication. Let discuss about the project, budget and timeframe in chat box Thanks, Shivpal S

@softsolution2000

I have extensive experience in Mobile App Development, iPhone, Android, C# Programming, and Face Recognition, making me well-equipped for the Smart Photo Selector App project. I am confident in delivering accurate face clustering, customizable photo filters, and seamless sharing functionality. The budget can be adjusted based on the project scope, and my focus is on meeting your requirements efficiently. Please review my 15-year-old profile to see my past work. I am eager to start working on this project and demonstrate my dedication.

@kamran2012

Good to see this project, I will build the photo selector app with on-device face clustering, three-filter selection (individual, date range, geolocation), and system share sheet integration. The face grouping will use Apple Vision / Google ML Kit for on-device processing to keep photos private — no server uploads needed. For accuracy, I will implement a confidence threshold so uncertain matches go to the "Unsorted" bucket automatically, with a simple drag-to-correct interface for manual fixes. This keeps false positives minimal without losing any photos. Questions: - Should this be iOS-first, Android-first, or cross-platform from the start? - For geolocation filtering, do you want a map-based picker or a location name search? - Do you need the app to handle libraries with 10K+ photos efficiently, or is the typical use case smaller? Send me a message and we can go over the details. Best regards, Kamran

@vishal1145

Your face-clustering accuracy will depend entirely on how you handle edge cases like partial profiles, poor lighting, and aging across photo timelines. Most developers implement basic face detection and call it done - then you discover it groups siblings together or splits the same person into three clusters. Before architecting this, I need clarity on two things: What's the largest photo library you expect to process (5K photos vs 50K makes a massive difference in memory management), and do you need real-time clustering or can the initial scan take 2-3 minutes on first launch? Here's the architectural approach: - VISION FRAMEWORK + CORE ML: Use Apple's VNDetectFaceRectanglesRequest combined with VNGenerateFaceObservationRequest to extract 128-dimensional face embeddings, then apply DBSCAN clustering with a tuned epsilon threshold that reduces false positives by 70% compared to naive k-means. - OPENCV FALLBACK: Implement Haar Cascade detection for Android devices where ML Kit struggles with side profiles, storing face descriptors in SQLite with spatial indexing for sub-second retrieval across 20K+ photos. - GEOLOCATION FILTERING: Parse EXIF metadata using ImageIO framework and build a MapKit interface that clusters pins by proximity - tapping a region instantly filters to photos within that radius without re-scanning the library. - INCREMENTAL PROCESSING: Use background threads with NSOperationQueue priority inversion handling so the UI stays responsive while processing 100 photos per second, storing intermediate results in Core Data with automatic migration support. I've built similar photo analysis systems for 2 consumer apps that processed 500K+ images daily. The tricky part isn't face detection - it's handling memory pressure when users have 40GB libraries and ensuring the clustering algorithm doesn't drift over time as new photos arrive. Let's schedule a 20-minute call to walk through your expected photo volumes and discuss whether you need cloud backup of face groupings or if everything stays local. I don't start builds where the performance requirements are ambiguous.

@pinkeegupta

Hi I have read your requirements and I am sure 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 , java spring boot and php CodeIgniter mvc. Please consider me and initiate a chat for further detailed discussion. Regards, Anju

@Rajoriadares

Hello Client, Greeting of the day!!!! I read your job description I have sound of five years plus experience in App development. I have been DEVELOPED 35+ Apps, three taxi apps, Two socials apps and restaurant apps based on GPS location and notification functionality and based on different domain like sports, Health, GYM, personal business and social etc I have testing team for testing apps. I think I am strongest person for doing this job and provide the quality product with testing. I am always available for your support. Thanks Sr. Mobile Developer

@rbtech1984

Hello There!!! ★★★★ (Smart Photo Selector App) ★★★★ I understand you need a mobile app that scans the camera roll, clusters faces of the same person, and lets you select photos via individual, date range, or geolocation filters before sharing. Accuracy in face grouping with minimal false positives is key, and uncertain matches should go to an “Unsorted” bucket. Services mentioned here based on project details ⚜ Automatic face detection and clustering using Apple Vision/Core ML or Google ML Kit ⚜ Manual correction for misclassified photos ⚜ Filters for selecting photos individually, by date range, or by geolocation ⚜ Efficient on-device processing to ensure privacy ⚜ Share sheet integration for sending selected images via any channel ⚜ Cross-platform development if needed (Flutter/React Native) ⚜ Source code delivery with setup instructions With 9+ years experience in mobile app development, iOS/Android, and photo management apps, I focus on reliable, user-friendly solutions. I would use ML Kit or Core ML for clustering, native filters for selection, and system share sheets for exporting. I’d love to discuss your requirements in detail and start building a clean, efficient, and private photo selector app for you. Warm Regards, Farhin B.

@ixorawebmob

Hello, I’ve gone through your project details and this is something I can definitely help you with. With over 10 years of experience in mobile app development, including face recognition and photo filtering, I’m well-equipped to build an intuitive Smart Photo Selector App. My expertise with Flutter and native development frameworks will enable me to implement the face clustering features you need while ensuring accuracy to minimize false positives. I focus on clean architecture and reliable user experiences, particularly in implementing efficient workflows, which is essential for your app's filtering and sharing functionalities. 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 features would you like to prioritize in terms of user experience? Let’s discuss over chat!

@abhisaini0188

Hello, As a seasoned web and mobile application developer with over 10 years of experience, I can confidently say that delivering your desired smart photo selector app is right up my alley. My expertise spans across multiple facets of development including strong frontend, backend, cloud, AI/ML, and ERP systems. Your requirement for efficient face detection and photo filtering aligns perfectly with my skills and my commitment towards creating scalable, secure, and AI-powered solutions. To add more value to your project, I bring with me a substantial know-how in AI and Machine Learning integration. I see excellent potential for incorporating this in your app for automating your face recognition process yielding accurate results with minimal false positives while ensuring utmost privacy for your photos. A few merits about working with me worth mentioning are: a clear focus on quality and performance; clean, maintainable code; proactive communication; punctuality in delivery; hands-on support throughout the project lifecycle. Choosing me translates to choosing an experienced partner who will not only deliver on time but also tirelessly contribute their expertise to optimize the end product tailored specifically to your requirements. Let's embrace this opportunity to turn your vision into a reality together! With Regards!

@Herculesz

Hi I can build your app with reliable on-device face clustering, clean photo filters and native share-sheet integration, ensuring complete privacy and fast local processing. The biggest technical challenge is grouping the same person across varied angles, lighting and ages, and I solve this using Vision/Core ML or ML Kit embeddings with a confidence threshold that pushes uncertain matches into an “Unsorted” bucket. The interface will make it easy to select photos individually, by date range or by geolocation, and allow you to combine filters for precision. You’ll be able to correct any cluster manually, and the app will instantly update groupings. Once your final selection is ready, the app will hand everything off to the system share sheet so you can forward images through any installed channel. Clean, well-documented source code will be included for local compilation and testing. Thanks, Hercules