Opencvproiecte

...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, ...

...exact same model, exact same results, but with modern syntax, clear separation of concerns, and thorough inline comments. You’ll start from my original scripts and checkpoints, preserve every bit of accuracy, and hand back a fully functioning module (including a simple demo script) that can be installed with pip-installable requirements. Feel free to streamline library calls—TensorFlow, PyTorch, OpenCV, or whatever is currently in place—so long as the final inference output matches the reference I provide. Deliverables • Refactored Python package replicating the current predictions on a supplied test set • README covering setup, dependencies, and usage • Quick comparison report showing identical mAP or better against the original run I&rs...

... Generate a ready-to-print shipping label (standard 4x6 thermal format). 2. Push the full XML payload to our in-house system through a REST-style API. I expect the software to run unattended on Windows, include simple UI panels for device status and manual override, and log every transaction for traceability. Code can be in C#, Python or another language suited to serial/USB device control, OpenCV and Tesseract OCR; just keep external dependencies to well-supported, licence-friendly libraries. Deliverables • Executable application and source code • Sample XML output reflecting the required structure • API endpoint documentation showing request/response examples • Deployment guide for connecting the scale, volumetric camera and scanner Accuracy, sp...

...pattern types: extend recognition beyond the basic horizontal/vertical stripes to oblique, curved, or irregular banding the current code ignores. • Optimize performance: refactor the pipeline for faster image loading, GPU-aware inference, and leaner memory use so it remains responsive on large datasets. Everything runs in Python, so please stay within that ecosystem. You are free to introduce OpenCV, scikit-image, PyTorch, TensorFlow, or other libraries, provided the final solution installs cleanly with a and runs from a single entry-point script or Jupyter notebook. Input will be folders of images; no video or live feed integration is required at this stage, but laying groundwork for future expansion is a plus. I will supply a labeled image set for benchmarking and exp...

...seconds, and push actionable alerts through a cloud-hosted pipeline. Later phases will weave in IoT sensors, GPS data and public-transport schedules, but for now cameras take centre stage and all processing happens in the cloud. Here’s what I need from you: • A complete stream-to-insight workflow: camera feed ingestion → cloud message bus → analytics micro-service. • Computer-vision models (OpenCV, YOLO, TensorFlow—your call) that flag incidents with >90 % precision/recall on my test clips. • A REST API that surfaces live traffic state and returns diversion routes in real time. • Extension hooks so I can sync bus, train and metro timetables and forward delay alerts to commuters. • Containerised or serverless deployment s...

...needs to handle: - Banking interactions (finding banker, opening interface) - Withdrawing logs - Walking to firemaking spots - Lighting fires - Managing inventory I have plenty of screenshots and reference images to work from, so you won't be starting from scratch! What I'm looking for: I need someone who's: - Really comfortable with Python on macOS (not just Windows/Linux) - Has experience with OpenCV or similar computer vision libraries - Has built game bots/automation scripts before - Understands how to make mouse movements and clicks look human (not robotic!) - Knows their way around Git Bonus points if you: - Have a background in ML or computer vision - Have experience with OSRS or similar games - Know macOS UI automation inside and out - Have thought about...

...provides the mathematical baseline — the system blends both outputs Implement smart caching and pre-computation so API latency doesn't slow down decision-making (pre-fetch likely scenarios, cache common spots) Fallback logic: if the API is slow or unavailable, the bot defaults to the GTO baseline so it never stalls mid-hand 2. Screen Reading / Game State Extraction (The Eyes) Use computer vision (OpenCV + Tesseract OCR or similar) to read the poker table from screen captures or browser window Must accurately extract: hole cards, community cards, pot size, stack sizes, player positions, betting actions, blinds/antes, tournament stage Card recognition model (CNN or template matching) with high accuracy Must work reliably across at least one major free poker platform ...

...Standard user and Guest—each with appropriate permissions for running detections, reviewing results and managing data. Please structure the code so that REST endpoints are cleanly separated; this will let me expose the following Android-ready APIs later on: live-video analysis, image-file analysis and retrieval of disease-history logs. Deliverables • Python inference engine (TensorFlow/PyTorch + OpenCV acceptable) optimised for Raspberry Pi 5 • Django project with the described role system, templates and REST endpoints • Model-training notebook or script plus labeled dataset reference • Setup script or Dockerfile for one-step deployment on a fresh Pi • Brief README covering install, usage and endpoint documentation Acceptance criteria ...

...pixels themselves • Contrast between those pixels and adjacent pavement pixels • A distance weighting that values pixels closer to the camera more heavily than distant ones • A continuity penalty that reduces the score when the mask reveals breaks or flicker in the lane line Feel free to propose additional minor refinements if they improve stability, but please keep the core idea intact. OpenCV, NumPy, and scikit-image are the tools I already use elsewhere, so sticking to that stack will make adoption easiest. The code should be clean, modular, and fast enough to process typical 1080p sequences in real time or near real time on a modern CPU (GPU use is optional but not required). Deliverables • A self-contained Python module or notebook that loads...

...phone while triggering audible deterrents on-site. Here’s the shape of the work: • System architecture: advise on the right combination of sensors (camera, PIR, ultrasonic, mic), onboard processing (Raspberry Pi, Jetson, or similar), and wireless protocols so the robot can run edge-based computer-vision without relying on the cloud. • Detection pipeline: develop or integrate a lightweight model—OpenCV or TensorFlow-Lite is fine—that reliably flags human intrusion in low-light and daylight conditions, minimising false positives from pets. • Alert mechanism: build the software bridge to push break-in alerts through a companion mobile app/API along with timestamped snapshots or short clips. A local siren should activate simultaneously. •...

...and remote fitness routines, there is a pressing need for intelligent systems that can guide users to perform exercises safely and effectively, minimizing the risk of injury and promoting consistent form. The proposed system leverages advanced computer vision and machine learning techniques to detect and analyze body posture using a live camera feed. By utilizing frameworks such as MediaPipe and OpenCV, the assistant accurately captures skeletal landmarks and evaluates the user’s movement patterns in real time. The AI model processes this posture data to identify deviations from the correct form and delivers immediate corrective suggestions. This not only enhances the effectiveness of workouts but also reduces the chance of developing injuries due to poor form. The system i...

...colour histogram (or any other standard colour-profile information we agree on), and write the numeric results to a clean CSV file. I care as much about the code organisation as the actual extraction: classes, clear method separation, doc-strings and a simple command-line entry point are expected so I can drop the module straight into a larger .gal-based workflow. Feel free to rely on Pillow, OpenCV, NumPy or similar mainstream libraries as long as dependencies are listed in a requirements.txt. Deliverable • A self-contained Python package (Git repo or zip) with class-based implementation • One example script showing how to point it at a TIFF and produce the CSV • Sample CSV output generated from my test image I’ll test by running the script on the p...

...whose text is now so heavily blurred that it is impossible to read. My only goal is to recover that text with enough clarity that every character can be copied or transcribed without guesswork. Because the blur is severe, I expect advanced de-blurring techniques—whether that means frequency-domain restoration in Photoshop, AI-powered tools such as Topaz Sharpen AI/Gigapixel, or custom Python/OpenCV scripting. Feel free to combine multiple passes or layer-based masking if that gives the best result; I just need the cleanest, most legible outcome you can achieve. Deliverable: a high-resolution image (PNG or TIFF) where the text is crisp and readable. If the restored file must remain at its original dimensions, please provide a second upscaled version for easier printing. ...

...artifacts). * Uniform/Badge Recognition: Detect if the person is wearing a police uniform or showing a badge (using object detection like YOLO). * Real-Time Risk Dashboard: * A simple UI that displays a "Trust Score." If the score drops below a threshold, it shows a "SCAM ALERT" warning. Preferred Tech Stack: * Language: Python * ML Frameworks: TensorFlow / PyTorch / Keras * Computer Vision: OpenCV, MediaPipe * NLP: Hugging Face Transformers (BERT/RoBERTa for intent classification) * Interface: Streamlit or Flask (for the demo dashboard) Deliverables: * Source Code (well-commented). * A file for easy installation. * A short demo video showing the system detecting a scam attempt from a sample video file. * Documentation on the model architectur...

...Python and computer vision. The goal is to take raw mobile photos and automatically clean noise, sharpen details, fix color and convert them to 3d printable files. You’ll choose or design the model, train or fine-tune it, then wrap everything in a lightweight API that my mobile team can call in real time (on-device when feasible, cloud fallback when not). You should be completely comfortable with OpenCV plus deep-learning frameworks such as PyTorch or TensorFlow, and you know the trade-offs between traditional filters, GAN-based approaches, and modern super-resolution networks. Experience packaging models for CoreML, TensorFlow Lite or similar mobile runtimes will set you apart. I’m most interested in seeing what you’ve already shipped, so please include past ...

...file uploads, batch processing, and ensuring stable communication between frontend and backend. The AI model itself already exists; the task is focused on backend integration and functionality, not training a new model. Required Skills: Python & Flask (API development and debugging) Experience handling image uploads and batch processing Familiarity with AI/ML image pipelines (colorization, OpenCV, PIL, etc.) REST API integration with React frontends JavaScript / React (basic integration understanding) Budget: $125 (fixed price)...

...The freelancer may not reuse, resell, publish, or redistribute the work (in part or full) without my explicit written permission. - I retain the unrestricted right to use, modify, extend, commercialize, or open-source the work in any form. - Applying to this project implies agreement with these terms. Skills Required: - Computer vision / image processing - Vector graphics (SVG/DXF) - Python + OpenCV preferred - Sketch generation / pen plotter experience is a plus How to Apply - Please include: - Relevant past work (vector / sketch preferred) - Short description of your approach - Tools/libraries you plan to use - Applications without relevant examples will be ignored. Important Note: This is a validation task, not a full production build. Clarity and reliability matter more...

...compile printable or shareable PDF/CSV reports. • Internet access in stadiums is patchy, so every feature—playback, tagging, clip rendering, report generation—needs to function without a cloud connection. Workflow I will provide sample multi-angle files and a summary of the metrics coaches track (possessions, tackles, turnovers, scores, distance covered). If you already leverage FFmpeg, OpenCV, or similar libraries inside Electron or Qt, great—just keep the final interface intuitive for non-technical staff. Deliverables 1. Signed installers for Windows (.exe/.msi) and macOS (.dmg). 2. Source code with build instructions. 3. Short video demo showing multi-angle sync, a generated highlight reel, and a single-player report. Timeline I woul...

...clean, artifact-free H.264/H.265 versions at multiple resolutions. It should be efficient enough for batch processing on a single workstation but scale to a GPU server when required. • Recommend (and set up) an AI model suited to my animation goals, then wire it into the pipeline so I can move seamlessly from encoded footage to AI-augmented renders. Whether you lean on TensorFlow, PyTorch, or OpenCV is up to you—just justify the choice and document how to reproduce it on my side. • Provide concise documentation: command-line flags, filter graphs, model checkpoints, and any tuning parameters. I need to understand why each setting was chosen and how to tweak it for future projects. Acceptance criteria 1. A working FFmpeg script or shell command that hits my...

...Product X and receive a free Product Y, the sales type should be labeled "custom". The PDFs contain little or no embedded text, so the workflow has to start with reliable OCR—Tesseract, PaddleOCR, AWS Textract, or another engine you trust is fine as long as the accuracy is high. The ads come in different layouts, so the logic that pairs text regions with the right price blocks needs to be flexible (OpenCV or similar image-analysis libraries will probably help). I will supply several sample PDFs that reflect the typical variety. Deliverables • Fully-working source code and any helper scripts • A brief README with setup steps and command-line usage • A sample run that produces the requested CSV in standard comma-separated format Acceptance cri...

...images) straight into neatly structured Excel sheets with perfect accuracy. Now I need that very same reliability extended to Punjabi. The requirement is tough but clear: deliver an OCR module that handles scanned electoral rolls in Punjabi and pushes the data into Excel with better than 99 % accuracy. The current pipeline is built in Python, relying largely on classical OCR techniques and some OpenCV preprocessing; it does not depend on heavy machine-learning models, and I want to keep it that way as much as possible. If you must introduce lightweight AI tricks to hit the accuracy target, document them so they can be toggled on or off. Deliverables • A standalone Python script (or module) dedicated to Punjabi language and alphanumeric house numbers • Clear setup i...

...Product X and receive a free Product Y, the sales type should be labeled "custom". The PDFs contain little or no embedded text, so the workflow has to start with reliable OCR—Tesseract, PaddleOCR, AWS Textract, or another engine you trust is fine as long as the accuracy is high. The ads come in different layouts, so the logic that pairs text regions with the right price blocks needs to be flexible (OpenCV or similar image-analysis libraries will probably help). I will supply several sample PDFs that reflect the typical variety. Deliverables • Fully-working source code and any helper scripts • A brief README with setup steps and command-line usage • A sample run that produces the requested CSV in standard comma-separated format Acceptance...

I need a piece of software that plugs straight into the video stream coming from existing, off-the-shelf CCTV cameras and immediately adds deep-learning smarts. ...plus. Deliverables • Installable software (source + compiled package) that connects to standard RTSP/ONVIF camera feeds • Model training or transfer-learning pipeline that achieves high accuracy on my sample footage • Real-time alert module covering email, SMS, in-app and monitor popups • Setup guide and brief user manual I’m comfortable if you leverage frameworks such as Python, OpenCV, TensorFlow or YOLO, as long as performance remains near real-time on 1080p streams. Let me know your approach, estimated turnaround time and any prerequisites you’ll need from my side (e.g., l...

...control. The flow is straightforward: the camera streams infrared frames, the script tracks the pool width in real time, and the stepper motor turns to raise or lower power so the pool stays within a target size. All components are already wired and bench-tested; you can SSH into the Pi as soon as the project begins. Key features the code must ship with: • Real-time monitoring of the pool size (OpenCV or a comparable library is fine) • Auto-calibration routine that maps the width of the molten metal pool on first start-up or on demand • Error logging to a local file with timestamps for any camera drops, motor stalls, or anomalies Python is the language of choice, so please structure the project as a self-contained module with clear README instructions and...

...Chatbot summary response Tech OpenCV for preprocessing OCR using Tesseract or equivalent 3. Live CCTV Computer Vision (MVP) Input Image or short video clip Simulated live feed using video frames Detection Person detection Count people Basic classification: Patient (bed or resting posture) Visitor (standing or moving) Tracking Track movement across frames No identity recognition Emergency Detection Fire or smoke Crowd congestion Abnormal situations: Person lying on floor Sudden group gathering Visual Output Bounding boxes for people Circles or highlights for danger zones Annotated frames Chatbot Alerts Text-based alerts inside chat: “Crowd detected in corridor” “Fire detected near patient area” Tech Stack (Expected) Backend: Python Computer Vision: ...

I’ve been experimenting with ways to read the shot meter in NBA 2K directly from the screen and now need a complete, production-ready solution. The program must capture the game window in real time, use OpenCV (or an equally capable computer-vision library) to locate and track the shot-meter graphics, and then generate immediate feedback outside the game. No memory reading or modding—everything has to rely purely on pixels. Core detection target • Shot meter timing: identify the fill level, green window and release point with enough precision that I can act on the feedback while the shot is still in flight. Feedback channel I’m flexible: an overlay drawn back onto the game, a small floating window, or both are acceptable as long as the information appear...

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...Well-structured, heavily commented source code. • A clear README explaining setup, required libraries, and how to plug the solver into any headless or GUI browser flow. • A short demo script showing the solver beating at least ten consecutive slider challenges in real time. • Notes on how to retrain or tweak the solution when PerimeterX rolls out a change. If you lean on machine-learning libraries (OpenCV, TensorFlow, scikit-image) or algorithmic tricks (edge detection, template matching, motion simulation), mention your plan up front so I can provision the right environment. Success is when I can drop the code into my pipeline, point it at a page protected by , and watch it pass the slider puzzle reliably without triggering blocks or rate-limit errors.

...laser systems can read without post-editing. Scope of work • Analyse each TIFF, detect all relevant outlines, and generate a single-layer path that is free of double lines, gaps, or overlaps. • Supply the vectors in SVG or DXF (both if practical). • Keep scale, proportions, and corner fidelity intact so the parts cut exactly to spec. • Document any automated workflow you use (e.g., Python + OpenCV, Illustrator actions, Potrace) so I can reproduce results on future batches. Acceptance criteria • Paths import into my cutting software with no open nodes or self-intersections. • Tolerance ±0.1 mm from the source contour when measured at key points. • All delivered files named to match the original TIFFs. If you have prior exp...

...that can watch hours of raw footage and automatically carve it into clean rushes. The idea is simple: detect every meaningful scene change or pronounced camera movement, mark the in- and out-points, and hand back an ordered timeline I can drop straight into my editing suite. My tool stack is already defined: PyTorch Video for the deep-learning backbone, PyDetect for proven vision utilities, and OpenCV for the faster classical operations. If you prefer to wrap parts of the workflow in ffmpeg or similar, that’s fine as long as the core logic stays in Python and can be called through a clear API endpoint. Scope • Analyse full-resolution clips, spot scene boundaries and camera pans/tilts/zooms with high recall. • Spit out a JSON (or EDL if you’d rather) li...

...performance—my target is 99 % character-level accuracy across the entire page, not just names or voter IDs. Once Telugu is solid, we will roll the same approach out to the rest of the major Indian scripts (Hindi, Bengali, Marathi, Malayalam, Kannada, Assamese, Gujarati, Punjabi and Odiya), but this job is strictly about nailing Telugu first. What you’ll work with • Current codebase (Python, OpenCV, pytesseract, a few custom TensorFlow helpers) • A curated set of high-resolution scanned PDFs and images of Telangana and Andhra Pradesh voter rolls for training / validation • My existing language-agnostic pre- and post-processing modules, which you are free to tweak Key responsibilities 1. Train or fine-tune a Tesseract language data set (or an al...

...with the probability engine that outputs the forecast bars. • Month 3 – Polished, responsive front-end (React/Next or similar), role-based user accounts, CI/CD, automated tests, Dockerised deployment to my AWS account, and hand-over of clean, well-documented code. Technology choices are flexible as long as they suit production (Python-based back-end like FastAPI/Django or a Node alternative, OpenCV or equivalent for vision, and any LLM you’re comfortable orchestrating). Explain your preferred stack, prior CV/LLM examples, and how you’d structure the micro-services so we can agree on scope quickly. Every milestone is payable on working, tested deliverables pushed to a private Git repo and demonstrated on the staging server. When you reply, please outlin...

I’m looking to have a full-featured image editor built for Android. The app should let users: • make basic adjustments such as crop, rotate, and resize, • apply a variety of filters and effects in real time, and • carry out advanced editing with layers, masks, and spot-...essential, and performance must stay smooth even on mid-range devices. Please structure the code so I can compile it in Android Studio, and include clear README instructions along with all source files, assets, and third-party library references. If you’ve shipped similar imaging or graphics projects before, share a brief example and note any open-source components you plan to use (e.g., GPUImage, OpenCV). I’m happy to discuss UI mock-ups, icon sets, and any edge cases you fo...

...seconds, and push actionable alerts through a cloud-hosted pipeline. Later phases will weave in IoT sensors, GPS data and public-transport schedules, but for now cameras take centre stage and all processing happens in the cloud. Here’s what I need from you: • A complete stream-to-insight workflow: camera feed ingestion → cloud message bus → analytics micro-service. • Computer-vision models (OpenCV, YOLO, TensorFlow—your call) that flag incidents with >90 % precision/recall on my test clips. • A REST API that surfaces live traffic state and returns diversion routes in real time. • Extension hooks so I can sync bus, train and metro timetables and forward delay alerts to commuters. • Containerised or serverless deployment s...

...seconds, and push actionable alerts through a cloud-hosted pipeline. Later phases will weave in IoT sensors, GPS data and public-transport schedules, but for now cameras take centre stage and all processing happens in the cloud. Here’s what I need from you: • A complete stream-to-insight workflow: camera feed ingestion → cloud message bus → analytics micro-service. • Computer-vision models (OpenCV, YOLO, TensorFlow—your call) that flag incidents with >90 % precision/recall on my test clips. • A REST API that surfaces live traffic state and returns diversion routes in real time. • Extension hooks so I can sync bus, train and metro timetables and forward delay alerts to commuters. • Containerised or serverless deployment s...

... 1X2, BTTS, over/under) • name of the match or event If you can also pick up the ticket number or stake while you are already parsing the slip, feel free to include those columns, but they are optional. Input will always be an image—either dragged in, captured from a webcam, or selected from disk. Because of that, I expect you to rely on a solid OCR or image-recognition stack (Tesseract, OpenCV, EasyOCR or a similar library) so the software works with standard printed slips under normal shop lighting. Once the data is parsed, the program should automatically cross-check the event result (an open API or another lightweight method you prefer is fine) and decide the outcome of the bet. No manual typing should be necessary after the image is supplied. Acceptance cr...

...please design the pipeline with those hooks in mind. Preferred flow 1. Upload or API push of multiple images. 2. Server chooses or lets me choose an alternative viewpoint/crop (“camera cut”). 3. AI engine processes, saves, and returns one or more high-res JPEGs per source image. 4. Dashboard shows progress, queues, and download links. Tech notes Feel free to lean on Python, TensorFlow/PyTorch, OpenCV, or similar libraries, plus a modern front end (React or Vue) and cloud storage (S3, GCS, or equivalent). Clean, well-commented source code, deployment scripts, and concise setup documentation must accompany the final hand-off. Deliverables (acceptance criteria) • Web portal deployed on a test server and accessible via URL • Batch upload handling at least 2...

...engineer to turn raw sports footage into structured insight. The system you build will ingest live or recorded matches, lock onto the ball and key players, keep them centered with an intelligent zoom, and raise flags the moment a goal is scored or a significant positional change occurs. I expect you to stitch together proven object-detection or tracking APIs with your own PyTorch, TensorFlow, or OpenCV code so we hit production-grade accuracy without reinventing wheels. The pipeline should: • track players, the ball, and other relevant objects frame-by-frame, • adjust the crop dynamically so the action stays in focus, • recognise high-value events such as goals or point scoring, as well as nuanced player movements and formations, • expose clean, we...

I want a desktop-based vision solution that watches any TV, computer monitor, or public display in real time and notifies me the moment someone steps in front of it and tries to take a photo. The core may rely on YOLO or straight OpenCV or Any—whichever gives the fastest, most reliable detection. How it should work • A camera connected to my desktop continuously analyses the scene. • When a person holding up a phone (or clearly preparing to photograph) is detected, the system must: – Crop the frame (or short clip) so the person is centred. – Timestamp it. – Dispatch the alert simultaneously to Telegram, WhatsApp, and Email or Any platform. Key expectations • Sub-second latency between detection and alert. • Clean, wel...

I want a desktop-based vision solution that watches any TV, computer monitor, or public display in real time and notifies me the moment someone steps in front of it and tries to take a photo. The core may rely on YOLO or straight OpenCV or Any—whichever gives the fastest, most reliable detection. How it should work • A camera connected to my desktop continuously analyses the scene. • When a person holding up a phone (or clearly preparing to photograph) is detected, the system must: – Crop the frame (or short clip) so the person is centred. – Timestamp it. – Dispatch the alert simultaneously to Telegram, WhatsApp, and Email or Any platform. Key expectations • Sub-second latency between detection and alert. • Clean, wel...

I’m looking to have a full-featured image editor built for Android. The app should let users: • make basic adjustments such as crop, rotate, and resize, • apply a variety of filters and effects in real time, and • carry out advanced editing with layers, masks, and spot-...essential, and performance must stay smooth even on mid-range devices. Please structure the code so I can compile it in Android Studio, and include clear README instructions along with all source files, assets, and third-party library references. If you’ve shipped similar imaging or graphics projects before, share a brief example and note any open-source components you plan to use (e.g., GPUImage, OpenCV). I’m happy to discuss UI mock-ups, icon sets, and any edge cases you fo...

My in-house Video Management System already ingests live H.264 streams from multiple IP cameras positioned around large industrial sites. The next step is to embed two real-time analytics module...match is required for now—just accurate detection and high-quality face capture that I can archive or pass to other systems later. Acceptance criteria 1. ≥95 % plate read accuracy on my provided test set of Indian vehicles. 2. Face box IoU ≥0.8 against ground-truth on the same streams. 3. End-to-end latency (frame in ➜ metadata out) ≤300 ms at 1080p30. If you have prior deployments of OpenCV + TensorRT, YOLO-based detectors, EasyOCR, PaddleOCR or similar on Indian road footage, mention them when you respond; sample screenshots or short demo clips will help me sho...

I need an OCR component that plugs directly into our existing order-processing software and reliably reads supplier purchase orders that arrive as JPEG scans. The engine only has to recognise English, but accuracy must be high enough to extract line-item tables, dates, totals and supplier IDs without manual correction. You are free to build on Tesseract, OpenCV, or a deep-learning stack such as TensorFlow or PyTorch, as long as the final module returns structured JSON we can map to our database. Deliverables I expect: • Source code with clear build instructions • A small training/validation dataset plus instructions for expanding it • API documentation and a quick demo script • Brief report on achieved accuracy and how to retrain the model if vendor layou...