Opencv işler

Ekte belirtilen 25 soru 5 şıktan oluşan dikdörtgen şeklindeki optik formu telefon kamerası ile okuyacak bir uygulama yaptırmak istiyorum. Uygulama üzerinden önce kullanıcı sınavın cevap anahtarını girecek, ardından uygun görüntü işleme algoritması ile işaretlenen şıklar tespit edilerek doğru/yanlış/boş soru sayısı hesaplanmalıdır. Ek olarak her sorunun kaç kez doğru kaç kez yanlış ve boş işaretlendiği her tespit sırasında tutulmalıdır. Uygulama Android için geliştirilmelidir.

Ekte belirtilen 25 soru 5 şıktan oluşan dikdörtgen şeklindeki optik formu telefon kamerası ile okuyacak bir uygulama yaptırmak istiyorum. Uygulama üzerinden önce kullanıcı sınavın cevap anahtarını girecek, ardından uygun görüntü işleme algoritması ile işaretlenen şıklar tespit edilerek doğru/yanlış/boş soru sayısı hesaplanmalıdır. Ek olarak her sorunun kaç kez doğru kaç kez yanlış ve boş işaretlendiği her tespit sırasında tutulmalıdır. Uygulama Android için geliştirilmelidir.

Ekte belirtilen 25 soru 5 şıktan oluşan dikdörtgen şeklindeki optik formu telefon kamerası ile okuyacak bir uygulama yaptırmak istiyorum. Uygulama üzerinden önce kullanıcı sınavın cevap anahtarını girecek, ardından uygun görüntü işleme algoritması ile işaretlenen şıklar tespit edilerek doğru/yanlış/boş soru sayısı hesaplanmalıdır. Ek olarak her sorunun kaç kez doğru kaç kez yanlış ve boş işaretlendiği her tespit sırasında tutulmalıdır. Uygulama Android için geliştirilmelidir.

Ekte belirtilen 25 soru 5 şıktan oluşan dikdörtgen şeklindeki optik formu telefon kamerası ile okuyacak bir uygulama yaptırmak istiyorum. Uygulama üzerinden önce kullanıı her sorunun cevap anahtarını girecek, ardından uygun görüntü işleme algoritması ile işaretlenen şıklar tespit edilerek doğru/yanlış/boş soru sayısı hesaplanmalıdır. Ek olarak her sorunun kaç kez doğru kaç kez yanlış ve boş işaretlendiği her tespit sırasında tutulmalıdır. Uygulama Android için geliştirilmelidir.

Yolo ve opencv ile ıp kamera takibi ile nesneleri tanımlama. Araba,insan,hayvan...

Merhaba ayın sonuna kadar bitirmem gereken proje var Proje ise:Elimde stereopi(yani 2 kamera var) takılı bir raspberry var onun kameralarının kalibrasyonu kodu yazılıp kameralar da obje görüntüsünü takip ediğ objenin x y z(x,y degil) koordinat sistemi ekranda gö misiniz ? Rasberrye Pycharm yükledim opencv kutuphanesi ve numpy kütüphaneleri yardımcı olabilir . Lütfen dikkat edin iki kamera var tek kamera kalibrasyonu istemiyorum

Opencv ile yapılabilecek işler için çok fazla insan gücüne ihtiyacımız olduğundan çalışmamıza destek verebilecek arkadaşlar aramaktayiz

Merhaba, elektrik sayacı üzerinden kamera ile sayac ekranında yazan kW bilgisini 3-5 dk da bir alıp ilk ve son değer arasındaki farkı alıp üzerinde basit matematiksel işlemler uygulayacağım bir kod lazım. Sayacımın görüntüsünü dosyalara yükledim. Video görüntü ilede olabilir 5 dakikada bir fotoğraf çekerekte. Daha sonra basit matematiksel işlemler ile kW miktarını vergi oranları ile çarparak çıktı olarak TL cinsinden değer almak istiyorum

Belirli nesne/obje takibi yapan araç için rasberry pi ve webcam kullanarak bir takip etme projeni yapı,kompenentler hariç sadece kodlama kısmına ihtiyacım var.

Merhabalar, Fotoğraftaki 4 kenardaki kareleri algılamak ve içindeki dairelere göre hangi şık seçilmiş tespit etmek istiyorum opencv kullanılarak yazılması yeterli herhangi bir dil olabilir. Telefon kamerası kullanarak çekilmiş dolu bir optik form fotoğrafı size göndereceğim burda hangi şıkları işaretlendiğini dönen bi fonksyon yazmanız benim için yeterli başka birşey istemiyorum. İlgilenenler mesaj atarsa örnek repolar paylaşabilirim. Teşekkür eder, iyi çalışmalar dilerim...

raspberry pi python opencv ile görüntü işleme alanında bilgi sahibi birisi

raspberry pi üzerinde python opencv ile yazdığım kodumu dışarıdan butona basarak çalıştırmak istiyorum

raspberry pi üzerinde python opencv ile yazdığım kodumu dışarıdan butona basarak çalıştırmak istiyorum

merhaba arkadaşlar , bilgisayarımda çalıştırdığım python kodunu raspberry pi ye yükleyip çalıştırmak istiyorum , raspberry pi de python ve opencv kurulu , kod yükleme uzun sürmeyecektir birkaç ince noktası vardır ama ben tam anlamıyorum , çok acil yardımcı olur musunuz

There is a tray of Turkish delight lokum picture. I want to find center coordinates off all candies (lokums). Opencv Program have to give x,y pixel (coordinate) matrix sort of left to rigt and top to bottom. This three picture show all things.

There is a png1 (File1) which is a Brain MRI, I should find the Region Of Interest (ROI) with matlab or opencv. obtained the original brain part of the image must be saved as another jpg. All the algorithms and codes must be given to me. ------------------ Ekte bulunan Png1 dosyas? bir beyin MR görüntüsüdür. Bu görüntüden ilgi duyulan bölge analizi matlab ya da opencv ile yap?lmal?. Elde edilen beyin parças? farkl? bir jpg olarak kay?t edilmelidir. Kullan?lan tüm algoritma ve kod teslim edilecektir.

...Handle multi-page statements, varying templates, and common artefacts such as skew, shading, or mixed languages. • Expose the extraction workflow to my app through a simple Node.js function or REST endpoint that I can call with a file path and receive JSON. • Store results to MySQL once the JSON passes validation. Technology expectations I have no fixed preference on libraries: Tesseract, OpenCV, PDFPlumber, pdfminer-six, or a custom C++ wrapper are all acceptable as long as the final stack remains 100 % on-prem. Optimising accuracy with pre-processing (deskew, denoise) and template detection is critical, and I’m open to using GPU acceleration if it simplifies heavy workloads. What I’d like from you Send a concise, detailed project proposal that ou...

I need a Raspberry Pi programmed so it can take a live video feed from an attached camera, run image-recognition on each frame to spot custom objects or patterns that I will later define, and then publish the resulting data over Modbus TCP. Here is the flow I am after: 1. Camera streams video into the Pi. 2. Your code performs real-time detection of the specified custom objects/patterns (OpenCV, TensorFlow Lite, or another light framework is fine as long as it runs smoothly on the Pi). 3. For every detection event—or on a set interval if no object is found—you convert the recognition result into register values and expose them through a Modbus TCP server running on the same Pi. Deliverables • Fully commented source code (Python preferred) • A br...

...multiple video files • Automatic video merging • Frame-difference / motion-based analysis • Automatic removal of low-motion segments • Export condensed MP4 video • Simple timeline interface for manual trimming • Basic text/overlay insertion No cloud required initially — local processing is preferred. ⸻ Preferred Tech Stack (Open to Suggestions) Backend / Video Processing: • Python • OpenCV • FFmpeg Frontend: • Electron / Tauri • React or similar Must support: • Windows and Mac • Efficient handling of large files (up to 5GB) ⸻ Project Type MVP development with potential long-term expansion into: • Advanced AI • SaaS platform • International commercialization I am looking...

...o fluxo. Funcionalidades indispensáveis • Confirmação imediata do agendamento, exibindo todos os detalhes recuperados do portal assim que a vaga for garantida. • Reagendamento rápido, permitindo selecionar novas datas/horários com poucos cliques, sempre que surgirem slots mais convenientes. • Módulo de reconhecimento facial integrado para validar identidade antes da submissão (pode usar OpenCV ou biblioteca similar). • FAQ automatizado dentro do app para orientar o usuário sobre passos, possíveis mensagens de erro e boas práticas. Esperado como entrega 1. Código-fonte bem organizado (script e app) com instruções de instalação. 2. Demonstra&cce...

...a neatly laid-out A4 PDF must be produced automatically. One wagon per page, with a frame grab of the video, the captured fields already filled, and space left for handwritten or typed comments. The PDF has to save locally and be shareable through the Android share sheet, ready to print without scaling issues. I am happy for you to rely on Android Studio, Kotlin or Java, CameraX, ML Kit OCR or OpenCV—whatever delivers reliable scanning and a clean, responsive UI. Accuracy and speed come before flashy graphics. Deliverables • Release-ready APK • Complete Android Studio source project • A4 PDF template and code that fills it dynamically • Brief setup/user guide Acceptance criteria • At least 90 % successful extraction of all three data grou...

...camera (USB or built-in), and immediately see bounding boxes with class names and confidence scores updating on-screen at 30 fps or better. Key details • Model: start with an existing YOLO checkpoint (v5, v7, v8 or YOLO-NAS—whatever you feel offers the best speed / accuracy trade-off). Feel free to fine-tune if that improves precision, but the core must stay YOLO. • Language & libs: Python 3.x, OpenCV for video capture/rendering, torch or ultralytics for inference. • Platform: Windows 10/11 desktop, runnable from a single installer or clean virtual environment; no cloud dependencies. • Output: highlighted video stream plus a lightweight UI panel that shows FPS, tool class counts and a “save frame” button for manual snapshot expor...

AI Image Generation Automation MVP ## 1. Project Goal Build a scalable AI image generation progran using AdsPower, Playwright, and Supab...and indices. 2. **Worker Implementation:** Build the script to read 400 prompts from the DB and save indexed images to local/cloud storage. 3. **Failure Handling:** Implement the logic to re-run only the specific indices that failed. 4. **Minimal UI:** Create a simple dashboard to upload prompts (CSV/Excel) and view the status of each index. ## 5. Strictly Prohibited - **No Image Recognition (OpenCV):** Use only DOM Selectors for reliability. - **No Manual Captcha Solving:** Use persistent manual sessions or 3rd party solvers if absolutely necessary. - **No Synchronous Processing:** All tasks must be processed via an asynchronous Worker-Queue ...

...video generation logic—transitions, basic trimming, and soundtrack alignment—so the user can go from assets to finished output with minimal clicks. • Include real-time or near-real-time preview plus the option for manual tweaks (simple timeline edits, text overlays, color adjustments). • Deliver clean, well-commented code—Python preferred—with clear instructions for installing dependencies (OpenCV, PyTorch/TensorFlow, FFmpeg, or any libraries you choose). • Provide a short demo video and sample input–output files showing the system working end-to-end. Acceptance criteria 1. Feed the system a folder of mixed MP4 clips and JPG/PNG images; receive a coherent, 1080p final video without crashes. 2. Key events (e.g., faces speakin...

J’ai une séquence vidéo de 1 minute en définition standard dans laquelle la plaque d’immatriculation d’un véhicule reste illisible. Mon uni...caractères exacts de cette plaque. Je fournirai le fichier original (format MP4) ainsi que le time-code approximatif où le véhicule apparaît. J’attends en retour : • l’image ou le court extrait optimisé où la plaque est lisible, • la transcription claire des caractères, • un court mémo sur les techniques utilisées (par exemple : stabilisation, upscaling IA via Topaz Video Enhance AI, filtres OpenCV, traitement Adobe After Effects, etc.) afin que je comprenne la fiabilité du résultat. M...

...charts of vitals. • Alert panel for out-of-range values. • Patient info card: Name, ID, Date. 4. Upload Interface • Web upload form (drag & drop or file select). • Trigger OCR → dashboard update. 5. Demo-Ready Hosting • Hosted on AWS EC2/S3 (or equivalent). • Fully clickable end-to-end flow: upload → extract → dashboard → alerts. ⸻ Tech Stack (Suggested) • OCR: AWS Textract / Tesseract / OpenCV • Backend: Python + FastAPI • Database: Postgres or SQLite • Frontend: React.js + / Recharts • Hosting: AWS ⸻ Requirements • Proven experience with OCR / Document AI projects. • Experience in Python backend + React frontend. • Must deliver a fully working demo in 7 days. &bul...

My MP4 clip is under one minute long, shot on a poor-quality security camera, and shows just one car. I must know its licence plate with absolute certainty for an insurance claim, so anything less than 100 % accuracy is of no value to me. I am looking for someone who routinely works with forensic video tools such as Amped FIVE, VideoCleaner, OpenCV pipelines, Topaz Video AI or comparable software to extract a crystal-clear, fully readable still. De-blurring, super-resolution, frame stacking—whatever it takes—is expected, provided the end result is court-defensible. Deliverables • A high-resolution still image of the plate (PNG or TIFF) • The enhanced video segment in a lossless format • A brief technical report (PDF) describing the methods and settin...

...context, and presents step-by-step on-screen cues and explanations. • A simple dashboard where I can script or edit each tutorial flow without touching code. • Solid architecture documentation so the solution can later expand into additional features such as multilingual support or automated editing. I’m open to whichever stack you recommend, though I anticipate computer-vision tools (e.g., OpenCV), an LLM integration (OpenAI, Anthropic, etc.), and a lightweight web interface (React, Vue, or similar). Please explain how you plan to: 1. Detect relevant moments in the video. 2. Trigger conversational tips or guided overlays. 3. Keep latency low so guidance feels instantaneous. Along with your approach, include timelines, any required APIs or licenses...

...should open the standard share sheet so I can send the chosen files through any installed channel (Messages, WhatsApp, AirDrop, e-mail, etc.). Accuracy is key: false positives in face grouping must be minimal, and whenever the algorithm is unsure, it should simply place the photo in an “Unsorted” bucket so I can manually move it. I’m happy for you to use Apple’s Vision/Core ML, Google ML Kit, OpenCV or another proven face-clustering library—whatever offers reliable on-device processing and keeps users’ photos private. Deliverables 1. A fully functional mobile app (native or cross-platform) that runs on at least one major platform. 2. Automatic face clustering with an easy way to correct mistakes. 3. Filters that let me select photos ind...

...architecture so multiple spas can use their own branding. • HIPAA-friendly storage practice for images and reports (no protected health info beyond the photo). • Admin capability to tweak the recommendation rules without redeploying code. • Clean, mobile-first UI; React or Vue on the front end is fine, but I’m open to other modern stacks. • Back-end could be Python (FastAPI, TensorFlow, OpenCV) or another language you prefer as long as the model can run securely on my server or via a trusted API. Deliverables • A fully deployed MVP on my cloud account (AWS or GCP). • Source code in a private repo with build instructions. • Trained/finetuned model or documented API connection. • Brief user guide and 30-minute hand-off ...

...sets. • Concise visual summaries—charts for the text, heat-maps or feature plots for the images—exported in high-resolution formats I can drop straight into presentations. • A short written report (PDF or Markdown) highlighting key findings, unusual correlations and any recommendations that emerge from the analysis. Feel free to lean on standard libraries such as pandas, NumPy, NLTK/spaCy, OpenCV or PyTorch-based utilities—whatever helps you surface meaningful insights quickly and reproducibly. If you have other preferred tools that suit mixed unstructured data, I am open to them so long as the final deliverables remain easily reusable. I’ll supply a structured folder containing sub-directories for /text and /images along with a brief data ...

...integrity is proven. Acceptance criteria 1. JPEG carrier image quality loss is visually negligible. 2. Embedded image can be fully recovered without errors. 3. Consensus selection completes within the time frame you specify and uses minimal bandwidth. 4. All code runs on a standard laptop without proprietary dependencies. 5. document the result in a report Feel free to use Python, C++, OpenCV, or any other open-source stack you are comfortable with, as long as the final deliverables meet the criteria above and are easy to reproduce....

...target app, wait for it to load, populate the login screen and navigate onward until the signature page is reached and signed. I imagine a compact gantry or articulated arm driven by servos or steppers, guided by a microcontroller (Arduino, Raspberry Pi, or similar). Because the touch targets are fixed, a predefined set of coordinates should be enough, yet I’m open to an overhead camera and OpenCV calibration so the robot can self-correct for phone positioning or screen rotation. What I need from you 1. Detailed mechanical design files (CAD, STL or DXF) and a complete parts list. 2. Control firmware and higher-level Python/C++ scripts for motion, timing and any computer-vision alignment. 3. A repeatable procedure to store my PIN and app credentials securely on the...

...the cameras quite precisely. We then exported the camera data to JSON using a script, which we then imported into Colmap as the start poses. We spent a long time developing a script that correctly exports the poses and imports and uses them correctly in Colmap. I'm happy to make this script available. Also, the JSON containing the start extrinsics. We also calibrated each individual camera with OpenCV and have very precise intrinsics for each camera. This is also read and used by Colmap. I will also provide the JSON. Then we made a test recording with our rig. It's just over a minute long at 30fps and 4k resolution. The rig itself is stationary. We moved and panned the rig in the recording. This results in a lot of parallax and reveals many details in the images. I ...

...set of outfit suggestions, indicating why each piece flatters the user’s proportions, complexion and current tastes. • A lightweight dashboard lets me update trend data, brand catalogs and style rules without redeploying the app. Technology expectations The recommendation layer can be built with Python (TensorFlow / PyTorch) or a similarly capable stack, and computer-vision models (e.g., OpenCV, Mediapipe) will be needed to validate measurements from photos if users choose that option. The mobile front‐end may be native (Swift / Kotlin) or React Native / Flutter as long as performance remains smooth. Cloud hosting on AWS, GCP or Azure is fine; I’ll provide the keys. Deliverables • Model code, fully commented and trainable on new datasets •...

... push, or SMS—whatever integrates cleanly) when someone signs in, signs out, or when an unknown face appears • Report generation that can be filtered by date range, department, or individual employee, exportable to CSV and PDF • A webhook endpoint so our internal systems can consume every check-in or alert programmatically Feel free to choose the stack you are most productive with—Python (OpenCV, FaceNet, Flask/FastAPI), or a JS stack (, Node, React) are both fine—as long as deployment is straightforward on a standard cloud VM or Docker container. The model must run on-prem or in our private cloud; no third-party APIs that send images off-site. Acceptance criteria: 1. System recognises registered employees with 98 %+ accuracy under normal offic...

...should open the standard share sheet so I can send the chosen files through any installed channel (Messages, WhatsApp, AirDrop, e-mail, etc.). Accuracy is key: false positives in face grouping must be minimal, and whenever the algorithm is unsure, it should simply place the photo in an “Unsorted” bucket so I can manually move it. I’m happy for you to use Apple’s Vision/Core ML, Google ML Kit, OpenCV or another proven face-clustering library—whatever offers reliable on-device processing and keeps users’ photos private. Deliverables 1. A fully functional mobile app (native or cross-platform) that runs on at least one major platform. 2. Automatic face clustering with an easy way to correct mistakes. 3. Filters that let me select photos ind...

...dropped streams or timing errors. Deliverables 1. Full-stack code (frontend + backend) with clear instructions. 2. Admin panel: credential generator, calendar slot manager, download/playback of recordings. 3. Automatic email module wired to my custom SMTP. 4. Load-test report proving 10-user concurrency. 5. Assisted hand-off and live verification on my server. Tech is flexible—WebRTC, OpenCV, Node.js, Python, or similar—so long as the dual recording + gaze tracking works consistently in Chrome and Edge....

...identificar automáticamente al estudiante mediante esas columnas y leer cada burbuja para asignar la nota. • Guardar los resultados directamente en MySQL y permitirme consultarlos, exportarlos o corregir manualmente desde la misma GUI. El sistema debe correr íntegramente en mi servidor (sin servicios externos) y ser instalable con un script o contenedor. Me interesa que uses bibliotecas como OpenCV, Pillow o similares para el reconocimiento, y que el código quede bien documentado para poder ampliarlo después. cabe recalcar que las fotos seran tomadas por camara celular, tomando en cuenta que no siempre seran tomadas en un ambiente ideal, entre otros. Al finalizar espero: 1. Código fuente completo en Python. 2. Script de despliegue ...

...shelves are crowded. Key expectations • Real-time theft detection logic that raises an event or REST webhook the moment a suspicious removal is spotted • On-screen bounding boxes and confidence scores for detected grocery items and customers • Continuous customer counter with hourly CSV/JSON export • Installers or scripts for Windows 10/11 and Raspberry Pi OS, including all required Python, OpenCV, PyTorch/ONNX, CUDA (where available) dependencies • A simple dashboard that shows live feed thumbnails, current customer count, and the last N theft alerts • Clear instructions on adding new grocery SKUs later Acceptance will be based on: 1. Smooth 25-30 fps inference on 1080p streams under Windows with GPU, and ≥10 fps on Raspberry Pi...

...the visible subject, expands that shape by a configurable offset, and returns the resulting cutline as an SVG file. Auto-outline detection is the single most important processing step; edge smoothing and colour tweaks are nice-to-haves but not required for this phase. Here’s the flow I have in mind. A user hits /outline with a multipart upload, the API queues the image, runs the outline routine (OpenCV, scikit-image, or any library you prefer), inflates the path by the requested number of pixels or mm, then streams back plain-text SVG. A second, optional endpoint /health is enough for monitoring. The service must comfortably handle images up to roughly 30 MB without timing out. I’ll review the work against a small set of deliverables: • Fully-commented Python ...

I need a fully-packaged proctoring add-on that plugs straight into Moodle qu...toggle the feature, choose snapshot frequency, set violation limits, and enable or disable each alert type. After each exam, an instructor-facing dashboard must display every captured frame with an inline viewer, a one-click download option, and a clear violation summary per student. Code should follow Moodle development guidelines, rely on PHP/JavaScript and an open-source vision library such as OpenCV or a comparable lightweight alternative, and ship with: • Complete, well-commented source • Installation & configuration guide • Unit / functional test scripts • Support through final deployment on our production server Keep the solution modular so upgrades to future Moodle...

...the project grows—then save every relevant frame straight into a MySQL database. Each stored image must be linked to the corresponding frame number and any detection metadata so I can later query, filter, and analyse the results. Once the data is stored, I want a lightweight viewer that steps through the saved frames in order, overlaying the detection boxes so I can visually confirm accuracy. OpenCV for frame extraction and display is acceptable; YOLO, TensorFlow, or another modern model is fine so long as the code is clean, well-commented, and easy for me to retrain with additional classes. To keep the hand-off smooth, please include: • A self-contained Python 3 script (or module set) that performs detection, inserts frames into MySQL, and plays them back. • ...

...can build a production-ready model that listens to a baby’s cry, watches the paired video, and decides—reliably—whether the cause is hunger, discomfort, or simple attention seeking. Audio and video must be fused inside one architecture; running them in parallel but independently will not satisfy our accuracy goals. You may use the deep-learning stack you trust most (PyTorch, TensorFlow, Keras, OpenCV, torchaudio, etc.) provided the final network can run in real time on an edge device and be exported to ONNX or TFLite. I will share product constraints and a small proprietary data set; you will expand it through public sources or augmentation, perform rigorous cross-validation, and refine the model until we consistently exceed 90 % precision and recall on an unse...

...concept, but I now need the scene brought to life with responsive touch/gesture input through AR Foundation and polished 3D assets. Unity 3D (URP) will drive the core app, while MediaPipe or OpenCV will handle hand-tracking and gesture recognition. On the hardware side the code must remain portable to Raspberry Pi OS and Arduino-based prototypes, so a clean Python or Node.js bridge is essential. Here’s what I’d like you to deliver: • A Unity scene that compiles on Android and iOS, wired for AR Foundation with robust user interaction logic (tap, pinch, swipe, custom gestures). • Integration of MediaPipe/OpenCV scripts so gestures trigger in-app events with minimal latency. • A small library of optimized 3D models (Blender or Maya) that match...

...TensorFlow Lite / OpenCV / YOLO, etc.) • Demonstrate: 1. Live head tracking 2. Auto zoom in real time 3. Stable performance (≥15 FPS) Deliverables • Full source code • Build instructions • Short demo video showing real-time performance • Explanation of how this will later integrate with a custom camera SDK Once validated, this prototype will be integrated into our production system. Target Platform (Future Integration) Our production system will be: • Android-based smart mirror • Wi-Fi camera input (custom SDK) • C/C++ (NDK) + Java/Kotlin • Video resolution: up to 4K • P2P local streaming (no cloud) So experience with embedded/mobile video pipelines is important. Preferred Skills • Computer Vision / Machine Learni...

...After auto capture: * Show a preview screen of the captured image * Provide two actions: * Save → confirm and store the captured image * Retake → discard the image and return to live camera view * Ensure retake resets detection and overlay state Technical Requirements * Technology Stack: React Native with Expo * Use Expo Camera * Corner / black box detection using: * OpenCV (WebAssembly or Expo-compatible approach), or * Any optimized computer vision technique suitable for Expo * Must work on Android and iOS * Performance optimized for real-time detection Deliverables * Fully functional camera module with: * Live 4 black box detection * Green overlay confirmation on successful detection * Automatic high-resolution image capt...

...moments, trim away the rest, merge the highlights, and export a seamless final cut. While doing so it should apply modern, clean-looking filters and subtle visual effects—think gentle color grading, light motion graphics, and smooth transitions that feel current rather than retro or flashy. I’m open to the underlying tech stack as long as the result is reproducible. If you prefer Python with OpenCV and FFmpeg, or would rather leverage an environment like Adobe’s Sensei APIs, that’s fine; just outline your approach. What matters is that the pipeline can be triggered from a simple command or button press and deliver a ready-to-publish MP4 or MOV in vertical 9:16. Deliverables • A working script, model, or plug-in that completes the trim-merge-fi...

...straightforward: the program captures frames, an AI model spots the person, and a virtual stick signal (XInput, vJoy or a comparable driver) nudges the aim every frame so it stays centred. Smoothness and speed are critical. On a 1080p feed I’m aiming for roughly 60 fps with no more than 40–50 ms end-to-end latency, so techniques such as YOLOv8, TensorRT or a lightweight custom network combined with OpenCV screen capture should fit. You’re free to choose Python, C++, or another language as long as the final build runs reliably on Windows 10/11 without needing exotic dependencies. Deliverables • Windows executable with a small GUI (start/stop, confidence slider, aim-speed slider, hotkey toggle) • Source code and the pretrained model that recognises p...

...- Timing data can be mocked for MVP Highlights: - Automatically record each run - Generate short highlight clip after run - Play highlight before next competitor Tech Stack: - Python, OpenCV, YOLOv8 (or similar), FFmpeg / RTMP, Docker (optional) Deliverables: - Working MVP prototype - Source code (modular, documented) - Demo video or test livestream - Basic setup instructions Why This Project is Interesting: - Real-world AI application - Clear commercial potential - No vague AI promises - Opportunity to shape a real product from the start REQUIREMENTS: Tech stack (preferred, flexible) - Python - OpenCV - YOLOv8 (or similar) - FFmpeg / RTMP - Optional: Docker - Frontend UI can be minimal or skipped for MVP
 Deliverables - Working MVP prototype - Source code (modular, ...