Automated Bib-Recognition Video System

@ZohaibRoy

⭐⭐⭐⭐⭐ Create a Smart Video Solution for Marathon Bib Detection and Clips ❇️ Hi My Friend, I hope you're doing well. I’ve reviewed your project requirements and see you're looking for an automated solution for marathon bib detection and video processing. Look no further; Zohaib is here to help you! My team has successfully completed 50+ similar projects in video automation. I will create a system that detects bib numbers, generates clips, and sends them to runners seamlessly. ➡️ Why Me? I can easily build your end-to-end solution as I have 5 years of experience in video processing and automation. My skills include OCR, video editing, and database management. I also have a strong grip on technologies like OpenCV and TensorFlow, ensuring a high-quality outcome for your project. ➡️ Let's have a quick chat to discuss your project in detail. I can provide samples of my previous work and show how I can deliver your requirements efficiently. Looking forward to discussing this with you in chat. ➡️ Skills & Experience: ✅ Video Processing ✅ Optical Character Recognition (OCR) ✅ Real-time Video Editing ✅ Database Management ✅ API Integration ✅ Python Programming ✅ User Interface Design ✅ Automation Solutions ✅ Cloud Deployment ✅ Project Documentation ✅ Troubleshooting ✅ Communication Skills Waiting for your response! Best Regards, Zohaib

@Herculesz

Hi I can build this as an end-to-end race media system that ingests two camera feeds, detects bib numbers, selects the best angle, generates runner-specific clips, applies your sponsor overlay, and dispatches compressed videos through WhatsApp or a compatible messaging API. My approach would use a vision pipeline with OpenCV + PyTorch/TensorFlow for bib detection and OCR, FFmpeg for clip cutting and compression, a SQL or Firebase layer for bib-to-phone matching, and a very simple browser dashboard for volunteers. The main technical challenge is reliable bib recognition under motion blur, lighting changes, and partial occlusion, especially when two cameras see the same runner at different moments. I would solve that with camera synchronization, confidence scoring across both angles, bib tracking over a short time window, and fallback rules that choose the cleanest frame sequence before generating the final clip. The admin side can stay non-technical, with buttons for start/stop, resend/delete, CSV upload, logo swap, and a live queue showing detection confidence and delivery status. I also design these systems for near-real-time processing, stable race-day operation, and clear documentation so your team can run it without depending on code changes during the event. And I can help you so on by delivering a practical, ready-to-use system with source code, deployment scripts, and handover guidance. Thanks, Hercules

@hassannaweed4

Having worked extensively in the realm of automation, data management, and AI in Python, I can bring a unique perspective to your bib-recognition video system project. My expertise aligns perfectly with your core requirements: Advanced OCR or vision model development tuned distinctly for marathon race bib numbers, secure database connection setup, and automated file dispatching via WhatsApp. In terms of syncronized ingest from multiple HD cameras, my profound understanding of different camera codes and tackling angles will ensure optimal use of footage for precise runner recognition. I can create an automatedmprocess for cutting videos into individual participant clips, adding the sponsor logo overlay as specified, and dispatching them seamlessly to the respective runners via WhatsApp. Moreover, I understand the paramount importance of a user-friendly admin dashboard for easy event management by non-technical volunteers. I therefore propose a browser-based interface with simplified controls for functions like recording toggling, detection accuracy monitoring, and database maintenance. With me on your project, you can expect not just a working system but an optimized solution that gives your team full control, making it easy to edit and swap logos as needed.

@techplusintl

Hi, To create an end-to-end solution for detecting marathon bib numbers from video footage, I will use Python with OpenCV for accurate OCR and video processing. The system will synchronize input from two HD cameras and process the footage in near-real-time to generate individual clips for each runner. I will set up a database connection using MySQL to link detected bib numbers with phone records. The clips will include a logo overlay and be sent via WhatsApp using a messaging API. I will also develop a simple admin dashboard for non-technical users to manage recordings and clips easily. Could you please clarify which messaging API you prefer for the WhatsApp dispatch? Also, do you have specific hardware in mind for the cameras? Let's chat or share any additional details needed to start the project. Thanks!

@Feriver

Hello, I understand you need a complete automated system to detect marathon bib numbers, generate personalized clips with sponsor overlays, and send them to runners via WhatsApp or a future-proof messaging API. I have experience in computer vision, OCR, and video processing, allowing me to design a robust pipeline that ingests synchronized HD camera feeds, detects bibs accurately under varied conditions, and produces clean clips with minimal latency. I will implement a near-real-time workflow using OpenCV and a lightweight TensorFlow/PyTorch model for bib recognition, FFmpeg for automated clip trimming and overlay insertion, and a SQL or Firebase database linking bibs to phone numbers. A simple, browser-based admin dashboard will allow non-technical users to start/stop recording, monitor detections, manage clips, and update bib-to-phone mappings. Full documentation, source code, and a live handover session will ensure smooth operation on race day. Thanks, Asif

@FaizalShaik80

Hi, hope you are well. I have reviewed your project and noticed that it is very similar to a task I completed two months ago. I am an experienced and specialized freelancer with 6+ years of practical experience in Python, C++ Programming and I’m able to complete and deliver this project promptly. Feel free to visit my profile to check latest work and feedback from clients. Let us make this great together, please connect in chat. Warm regards.

@alizain721

Race-day tech must be foolproof for non-technical volunteers. I build end-to-end systems that a volunteer can run with one click. The best thing about me is I’ve worked on a very similar project recently, building a bib-detection pipeline for a city 10K that used two fixed cameras, real-time OCR, automated clipping with pre/post-roll, logo overlay, and automated WhatsApp delivery. I understand the full user flow: synchronized RTSP ingest from two HD cameras, per-frame bib detection and tracking, angle selection or merge for the cleanest frame, FFmpeg-based clip generation, overlay injection, DB lookup (SQL or Firebase) to map bib→phone, and WhatsApp or Twilio API dispatch. Proposed stack: OpenCV + PyTorch (CRNN/EAST + tracker), FFmpeg, Flask/React admin UI, optional GPU (NVIDIA T4/RTX3060) for near-real-time. Expected accuracy 90%+ with decent camera placement; higher with tuned model and good lighting. I can save you setup time because I’ve deployed and documented this flow before. Do you already have WhatsApp Business API access and what peak runners per minute should the system handle? Happy to chat or hop on a quick call to scope timelines and hardware. Regards Ali Zain!!

@Techroj

Dear Client, Greetings!! I have reviewed your requirements and can build a complete end-to-end system for bib number detection, clip generation, and automated delivery. With 7+ years of experience in Python, AI/ML, and computer vision, I wil use OpenCV with a custom trained OCR/CNN model for high accuracy bib recognition under motion and varied lighting, along with FFmpeg for precise clip extraction and overlay. The system will intelligently select the best camera angle, generate clips in near real time, and link detected bibs to phone records via a database . I will also imlpement automated WhatsApp delivery, along with a simple browser based admin dashboard for non technical users to control recording, monitor detections, manage data, and resend clips easily. The final solution will include full deployment, clean code, documentation, and a handover session. Hope to hear from you soon!! Regards, Rojan.U

@nemanjac6

Hello, you’re looking to build an automated bib‑recognition and clip‑delivery system, I’d handle it by structuring a backend pipeline that ingests dual‑camera streams, runs OCR detection, and triggers clip generation with automated messaging. The main constraint will be keeping processing reliable under motion and lighting variance. I’ve delivered similar computer‑vision pipelines with OCR + FFmpeg workflows and cloud‑based dispatch. I’d structure it like this: • Dual‑stream backend service handling camera ingest, frame sync, and bib‑event triggers. • OCR model (TensorFlow/PyTorch) tuned for bib patterns, with confidence scoring and data‑flow validation. • Clip generator using FFmpeg to cut segments, apply overlays, compress, and hand off to a WhatsApp‑compatible API. • Admin dashboard (browser‑based) for monitoring, retry logic, uploads, and logo management. A practical insight: using motion‑tracked ROI improves bib stability for higher OCR accuracy. Which camera angles or framing constraints (distance, height, lens type) do you already know so I can model OCR accuracy more precisely? Let me know if you want this broken down further. , Nemanja

@xoheruox

Hello, Now Meta is your company, leveraging a decade of proven expertise in Matching Job Skills. We have attentively reviewed the project's requirements for the development of an Automated Bib-Recognition Video System. Our team will follow a meticulous process that includes developing a custom OCR or vision model specifically tuned for marathon race bib numbers, synchronized ingest from two fixed HD cameras, real-time processing for quick clip availability, automatic clip generation with optional logo overlay, database connection for linking bibs to phone numbers, and automated WhatsApp dispatch of clips. We are ready to discuss this project further in a personalized chat to move it forward. Regards, Now Meta

@danielboggs

Hi, I’ve read your brief and can deliver an end-to-end bib-recognition and clip-delivery system that a non-IT volunteer can run on race day. I’ll build a lightweight pipeline using a tuned OCR/vision model (TensorFlow/PyTorch + OpenCV) for robust bib reads, FFmpeg for precise clipping, simple rules to choose the best angle from two cameras, and a small API service to match bibs to your SQL/Firebase records and trigger compressed WhatsApp messages via a messaging API. The admin is a minimal browser UI to start/stop capture, monitor detection, manage the bib-phone list and logo, and resend/delete clips. I’ll document deployment, recommended VM/hardware, and accuracy expectations from test runs. Next step: I’ll outline a short architecture diagram and a test plan so you can approve before I build. Do you already have sample footage and a current bib-to-phone spreadsheet I can use for tuning and end-to-end tests? Best regards, Daniel

@zahidhasta

Hi, This is a well thought out system and I understand the priority here is reliability on race day and simplicity for a non technical admin. I have built real time computer vision systems with video processing, OCR, and automation pipelines, so I can deliver this as a complete working solution, not just separate components. Here is how I would approach it: 1. Bib Detection and OCR I will use a custom trained detection model combined with OCR tuned for race bib formats. This improves accuracy under motion, blur, and varying lighting instead of relying on generic OCR. 2. Dual Camera Handling Both camera feeds will be ingested and synchronized. The system will automatically select the best frame or combine detections to ensure the clearest bib read. 3. Clip Generation Using FFmpeg and tracking, each runner will be detected and tracked, and clips will be generated starting a few seconds before detection and ending after exit. 4. Real Time Processing Pipeline will be optimized to process near real time so clips are ready within minutes. 5. Admin Dashboard A simple browser interface with start stop controls, monitoring, resend option, and easy CSV upload for bib to phone mapping. Designed for non technical users. I will keep the system stable and easy to operate so it works smoothly during the event without technical intervention. Best regards Zahid Hassan

@huonghy89

Hi, I hope you are doing well. Very happy to bid your project because my skills are fitted in your project. I have experience building end-to-end computer vision systems for video detection, OCR, object tracking, clip generation, and automated delivery workflows with simple web dashboards for non-technical users. I have also worked with OpenCV, PyTorch/TensorFlow, FFmpeg, OCR pipelines, database integrations, and messaging/API automation for production-ready event workflows. I will build a ready-to-use system that ingests both camera feeds, detects marathon bib numbers accurately, selects the best angle, generates individual runner clips, adds your sponsor logo, and sends compressed videos automatically through WhatsApp or a compatible messaging API. I will connect the detection pipeline to your SQL or Firebase database, and create a very simple browser-based admin panel where a non-technical volunteer can manage recording, review detections, resend clips, upload bib-phone data, and change the overlay logo. I will also provide a deployed prototype, full source code, clear documentation, an installation script, and a handover session, while advising you on practical hardware requirements and expected accuracy for race-day use. If you send the message, we can discuss the project more. Thanks.

@juanestebana17

Hello, With extensive experience in computer vision and video processing, I will develop a robust end-to-end system tailored for your marathon bib recognition needs. Utilizing advanced OCR and vision models, combined with synchronized multi-camera ingestion, I will ensure high accuracy even under challenging conditions. The solution will feature real-time processing, automated clip extraction, overlay integration, and direct WhatsApp delivery, all managed via a simple browser-based interface ideal for non-technical volunteers. What specific features or functionalities are most critical to ensure the system meets your race-day needs? Thanks, Juan Aponte

@adisonw

Dear Sir, I am thrilled to bid your project. This is a strong fit for me because it combines computer vision, video automation, OCR, database matching, messaging delivery, and a very simple admin workflow for non-technical users. I would build this as a practical race-day pipeline using Python with OpenCV/YOLO or OCR tuning for bib detection, FFmpeg for clip cutting and logo overlay, a small backend for queue processing, and a clean browser dashboard for volunteers. The system would ingest both camera feeds, choose the clearer angle per runner, generate a short clip around the detection window, match the bib to your phone database, compress the video, and dispatch it through WhatsApp API or a compatible messaging layer. I would also keep the admin side simple: upload spreadsheet, start/stop monitoring, resend/delete clips, swap logo, and review low-confidence detections. The key is building it for reliability and ease of use, not just as a demo. I’d like to go over a few points: Do you already have sample race footage from the exact camera setup so I can tune bib detection for real lighting, motion, and angle conditions? For WhatsApp delivery, do you already have access to an approved Business API provider, or should I set the system up with a provider-ready integration path from the start? Sincerely, Adison.

@linksProvider001

No pay until working demo is ready Unlimited revisions until you’re 100% satisfied I know how tricky it is to capture every runner perfectly and send clips fast without manual work — I can build this fully automated for you. Hi, I’m Muaz, Full Stack Developer with 6+ years experience. I will build your complete system: ✔ Accurate bib number detection (OCR + AI tuned for motion & lighting) ✔ Smart 2-camera sync to pick best angle automatically ✔ Auto video clipping (before + after runner appears) ✔ Logo overlay on every clip ✔ Database link (SQL/Firebase) to match bib → phone ✔ Auto send videos via WhatsApp API ✔ Simple browser dashboard (super easy for non-technical admin) Tech I’ll use (best for your case): Python, OpenCV, TensorFlow/PyTorch, FFmpeg, Cloud VM, REST APIs You’ll get: ✔ Ready-to-use system (race day ready) ✔ Clean code + setup guide ✔ Simple admin panel (start, stop, resend, edit data) ✔ Full handover session Let’s make this smooth and fully automatic for your event.

@Lazarone1

Hi, that’s great to hear! Your project closely aligns with one I recently worked. In that project, I built an automated sports‑event media pipeline using custom OCR models, multi‑camera synchronization logic, and a video‑clipping engine powered by OpenCV, TensorFlow, and FFmpeg with cloud-based messaging delivery, database matching, and a simple browser admin panel. Your marathon-focused requirements, bib detection under motion, two‑angle ingest, automatic clip trimming, logo overlays, and WhatsApp distribution, fit naturally within a similar architecture I’ve implemented before, and I can deliver a ready-to-use system suitable even for non‑technical volunteers. I’d be glad to connect and share my experience in more detail over chat. Thank you. Best regards, Lazar

@M2Guru

Hi, I have strong experience building practical computer-vision automation systems that combine OCR, video processing, database matching, and message delivery into a workflow that non-technical users can operate reliably. For this project, I would design the solution around bib detection accuracy, fast clip generation, dependable database/WhatsApp integration, and a very simple browser-based admin panel so race-day operation is smooth and realistic. I’m comfortable using tools like Python, OpenCV, FFmpeg, OCR/vision models, and lightweight web dashboards to deliver an end-to-end prototype that is usable in the field, not just a demo. I’m confident I can build a robust first version and document it clearly so your team can run it with minimal technical effort. Best Regards, Geoffrey Hoffman

@Ashnasajid

Hi, I can do this. I propose an end-to-end solution utilizing OpenCV and TensorFlow for accurate OCR tailored to marathon bib detection. The architecture will include two synchronized HD cameras, processing video in real-time to generate individual clips with a sponsor logo overlay. The system will connect to a SQL or Firebase database to match bib numbers with phone records, enabling automated WhatsApp dispatch of clips. A simple browser-based admin dashboard will allow non-technical users to manage recordings, monitor detection accuracy, and handle clip distribution. I anticipate achieving over 90% accuracy in varied conditions. For hardware, budget for two HD cameras, a robust server (8-core CPU, 16GB RAM), and sufficient storage for video processing. Deliverables include a fully functional prototype, source code with documentation, an admin guide, and a remote handover session. Looking forward to discussing this further. Ashnasajid