Tensorflowcông việc

...60–120fps, đồng bộ thời gian NTP/PTP. • Phát hiện và tracking bóng (AI: YOLO/RT-DETR). • Dựng quỹ đạo 3D, xác định thời điểm chạm đất (kết hợp audio). • Nội suy frame (optical-flow) khi chỉ có 60fps. • Tính toán điểm tiếp xúc và quyết định IN/OUT. • Xây dựng giao diện hiển thị cho trọng tài, replay video chậm cho khán giả. 3. Yêu cầu kỹ năng • Thành thạo Python, OpenCV, Deep Learning (PyTorch/TensorFlow). • Kinh nghiệm với YOLO/DETR/RT-DETR hoặc mô hình object detection real-time. • Triangulation, multi-view geometry, bundle adjustment. • Xử lý video nhiều camera, đồng bộ thời gian. • Ưu tiên: kinh nghi...

Tôi cần thuê người có thể thiết kế chrome extension kết hợp để nhận diện ảnh của 1 website bất kỳ khi mở lên. Lương 5 triệu khi xong app. Có thể thỏa thuận lại lương. [Removed by Freelancer.com Admin]

...a MEAN stack/Python developer. You will be helping us create and implement the following: • An adoption roadmap that ties specific AI capabilities to each stage of our workflow and project milestones, showing where automation, prediction, or generative content delivers the most value. • A reasoned “why this, not that” selection of tools—think Hugging Face transformers versus OpenAI GPT-4, TensorFlow or PyTorch for model training, spaCy for NLP, Vision APIs for image tasks—plus rapid prototypes that prove the choice. • Drop-in reference implementations or micro-services that slot straight into our existing Node/Express back end. • Plain-language docs and two-minute screen-share videos so community groups, national NGOs, and global...

...object detection model built, trained, and packaged so it runs smoothly on iOS and Android devices, in a modern web browser, and as a lightweight desktop application. The same model should power every platform to keep accuracy and behaviour consistent. You are free to choose the framework you are most comfortable with—TensorFlow, PyTorch, YOLOv8, Detectron2, or another proven library—as long as the final artefacts meet these requirements: • Mobile: optimised builds (e.g. TensorFlow Lite, Core ML, or ONNX) that hit realtime speeds on mid-range phones. • Web: WebAssembly/WebGL or implementation that loads in under three seconds on a standard connection. • Desktop: a small executable or Python app with GPU support when available and CPU fallb...

...levels—Admin, 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 Ac...

...coordinates so rescuers can be dispatched quickly. I’m flexible about the imagery source—NASA, ESA, Google Earth, or any other free feed is fine as long as it delivers cloud-free, high-resolution scenes on a daily cadence. You are welcome to mix sources when one is fresher than another. The detector has to work at desert scale, so please build it with an established computer-vision framework (e.g., TensorFlow, PyTorch, YOLO, or a similarly robust model) and output the findings in both human-readable (an image with bounding boxes or a simple web map) and machine-readable form (CSV/GeoJSON with lat/long, time stamp, confidence score). Once I can point the script to a new polygon and receive a list of car and truck coordinates every 24 hours—fully automated, no ...

...STACK ──────────────────────────────────────── ### Backend • Node.js (NestJS) OR Laravel • REST + WebSockets • PostgreSQL • Redis ### Fleet Core • Fleetbase (extended via plugins) ### Frontend (Web Dashboards) • React.js or • Tailwind CSS • Mapbox or OpenStreetMap ### Mobile Apps • Flutter (preferred) OR React Native ### AI & Analytics • Python • FastAPI • Pandas • Scikit-learn / TensorFlow (later phase) ### Payments • Stripe SDK • PayPal SDK • CMI API ### DevOps • Docker • CI/CD • Cloud hosting (AWS / GCP / Azure) ### Design • Figma (mandatory) • Design System • UX focused on minimal interaction ──────────────────────────────────────── 13. PROJECT EXPECTATI...

...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. • Navigation ...

...and renters. At its core the app must let a property manager add, edit, and remove listings (images, price, availability, basic details). The AI component should work behind the scenes—think auto-tagging amenities from photos, suggesting competitive pricing ranges, or surfacing the most relevant homes to a tenant based on their previous in-app behaviour. I’m open to the exact technique you use (TensorFlow Lite, ML Kit, embedded models, or a lightweight cloud call), so long as it stays responsive on typical mid-range Android devices. No third-party property-management or CRM integrations are required; the app should run as a self-contained product with its own lightweight backend or local data layer. A clean Material-style UI, Kotlin codebase, and modern Android archi...

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...adjusts intensity and volume to suit beginner through intermediate levels, and outputs a structured weekly routine (exercises, sets, reps, rest, and optional equipment notes). The system should justify its choices in plain language so the end user understands the reasoning behind each exercise block. I’d like the core to be written in Python, preferably leveraging familiar ML libraries such as TensorFlow, PyTorch, or scikit-learn—happy to hear your recommendation. Data sources for exercise selection can come from public, reputable fitness datasets or a curated ruleset you supply. The end result should be easy for me to integrate into a simple web or mobile front end. Deliverables • Clean, well-commented source code for the workout-plan generation engine &...

...with mobile app Mobile App Requirements Android & iOS compatibility (Flutter / React Native preferred) Login & user profiles Real-time notifications AI-based smart features Secure backend connectivity Preferred Tech Stack (Developers can suggest better alternatives) Frontend: React / / Vue Backend: Node.js / Django / Laravel Mobile App: Flutter / React Native AI/ML: Python, TensorFlow, OpenAI API, or similar Database: MongoDB / MySQL / PostgreSQL Cloud: AWS / Firebase / Azure Security Data encryption Secure authentication Role-based access (Admin/User) Deliverables Fully working website Mobile app (APK + iOS build) Admin dashboard Source code Deployment support Documentation Freelancer Requirements Proven experience in AI projects Portfolio of...

...for lack of blinking, lip-sync errors, or 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....

...just for them. My priority is customer engagement, so the core of the job is a recommendation engine that serves personalised promotional offers in real time, based on search intent, page behaviour and purchase history. Your job: • Examine my current site structure, content and analytics to see what data we can safely feed the model. • Build or configure an AI recommendation layer (Python, TensorFlow, GPT-based, or a proven SaaS solution—whichever you can justify) that plugs into the site and pushes the most relevant promo offer to each user. • Optimise on-page SEO signals so the personalised content also strengthens overall ranking without keyword stuffing. • Set up event tracking so we can measure uplift in click-through and conversion. •...

...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 work that proves you can take an image-processing idea from notebook to app store. Deliverables • Clean, well-commented Python codeb...

...for both iOS and Android. While the mobile build is underway, I also want to formalise the visual language of the product—colours, type, iconography, tone—into a concise brand style guide that my team can reuse across every touchpoint. Certain features in the roadmap rely on AI (for example, smart content recommendations and intent-based search). If you have preferred libraries or services—TensorFlow Lite, OpenAI, LangChain, or on-device ML kits—bring them into the discussion; speed of delivery is key. I’m comfortable with AI-assisted tooling (GitHub Copilot, automated testing, etc.) if it keeps the timeline tight. Once the mobile MVP is solid, I want a pared-down web companion built from the same React codebase wherever possible. A responsive ...

...free to abstract this behind a clean API layer so either provider can be swapped in later. • Send confirmation and reminder messages automatically, with hooks for SMS and email. Tech preferences I am most comfortable reviewing code written in Python, and I already run Docker in production, so please containerise the service. You are welcome to use libraries such as spaCy, Rasa, Dialogflow, TensorFlow or PyTorch—choose what fits the problem, document your reasoning, and make installation reproducible with a single script. What I will accept as “done” 1. A Docker-ised project that I can spin up locally, connect to my calendar, and watch it schedule a demo meeting end-to-end. 2. Clean, commented source code plus a concise README detailing setup, envi...

...Messaging is used for internal notifications and alerts. The system follows a serverless architecture where security rules are managed through Firestore rules. The architecture supports multi-tenant functionality with hospital-level data isolation. Artificial Intelligence Generative AI using the Gemini API is integrated for medical summaries and clinical analysis. On-device AI is implemented using TensorFlow Lite for offline disease classification and suggestion logic. Local JSON-based datasets are used for storing information about medications, precautions, and self-care guidelines. Core Features and Functionality Global and Common Features The system supports multi-role authentication including System Admin, Hospital Admin, Doctor, Receptionist, and Patient. Real-time notifi...

...train a powerful intrusion-detection model without ever sharing raw traffic logs. Each embassy keeps its packets local, trains an IDS in Python, then ships only the updated weights to a permissioned blockchain that averages them and sends back the enhanced parameters. Key points I need turned into code: • Dual-framework training loops: the local agent must be able to switch between PyTorch and TensorFlow so each site runs whichever stack its engineers prefer. • Attack coverage baked into the dataset pipeline: the IDS must correctly classify Malware, Phishing, and DDoS patterns. Synthetic generation for edge cases is fine as long as the final validation shows clear detection rates for all three. • Smart-contract aggregator: the chain’s sole responsibility ...

...throwing errors whenever it calls certain library functions. I need a sharp eye to dive into the code, pinpoint the exact cause, and leave me with a clean, reproducible fix. Here’s the situation as clearly as I can put it: • The faulty piece lives in a Python script that glues together key stages of the workflow. • The issue surfaces inside library-level calls—think NumPy, pandas, scikit-learn, TensorFlow, or similar. • Once corrected, the rest of the training and inference steps should run without manual work-arounds. What I’m expecting from you • A patched script that runs end-to-end on my side. • A concise changelog or inline comments explaining what broke and why your fix works. • Any environment tweaks (package versio...

I'm looking for an experienced Python teacher specializing in advanced programming and machine learning. Essential requirements: - Expertise in Python, especially in machine learning - Ability to explain complex concepts clearly - Experience with popular ML frameworks (e.g., TensorFlow, PyTorch) - Flexible scheduling to accommodate my learning pace If you have a strong background in these areas, please apply!

I need a wearable device to detect sleep-time bruxism. Requirements: - Monitors muscle activity. - Alerts with sound when clenching. - Collects clenching duration and frequency data. - Must reside in india ( bangalore) Ideal Skills: - Arduino/ESP32 development - Python/TensorFlow Lite (microcontrollers) - Embedded systems & electronics (mic setup, signal processing) Hardware can be procured by me or reimbursed. Urgent requirement

I’m ready to take my current WordPress-based platform and weave AI into its core so the site works harder—and smarter—without constant manual input. The overarching goal is “website AI integrated,” meaning the chosen solution should sit natively inside WordPress, draw on best-fit frameworks such as OpenAI, TensorFlow, or similar, and deliver tangible daily efficiencies. The three areas I want the AI to handle are: • Customer support chatbots – a conversational layer that resolves common questions, hands tougher issues to humans, and logs every exchange back into WordPress or our CRM. • Content personalization – dynamic page, product, or article recommendations driven by real-time visitor behavior. • Data analysis and rep...

I am rolling out a trio of inter-linked prototypes that tackle pressing urban and environmental challenges while showcasing cutting-edge AI, blockchain, and IoT engineering. First, the AI-driven Smart Traffic System must ingest multi-sensor feeds, apply real-time reinforcem...report comparing baseline vs. prototype performance Acceptance criteria – Source compiles and runs without modification on the stated platform – ML models reproduce stated metrics using provided data – Voting demo passes independent audit script – Traffic simulation shows ≥ 15 % average wait-time reduction If you need data samples, CAD files, or clarifications on preferred libraries (TensorFlow, PyTorch, ROS2, Hardhat, ), let me know early so I can share the assets and keep...

...tricks • Record results, visualise them clearly, and explain the “why” behind the numbers • Iterate on your findings until we have a result worth integrating into production-grade code What you should bring Your application only needs to highlight relevant experience, but that experience must show strong analytical and problem-solving skills. If you are already comfortable in Python, R, TensorFlow, PyTorch or similar stacks, say so—those tools are the basis of most of our work, though deep mastery is less important than the ability to dissect a problem and reason through solutions. Deliverables 1. Reproducible notebooks or scripts for each experiment 2. A concise report explaining methodology, results, and next steps 3. A short hand-off ...

A small TensorFlow script in my project has started throwing errors, and I need it back in working order within 48 hours. The bug sits somewhere between the data-loading step and model training; once you jump in you’ll have full access to the Python code, sample data, and the original (working) training logs so you can compare behaviours. I work entirely in Python and TensorFlow, with a handful of standard utilities such as NumPy, pandas, and Matplotlib. No other frameworks are involved, so deep familiarity with TensorFlow’s debugging tools, graph/symbolic APIs, and eager execution will let you move quickly. Here is what I expect at hand-off: • A corrected script that runs start-to-finish on my machine (TensorFlow 2.x, Python 3.9). • A concise...

I'm seeking an AI/ML expert to develop a smart health ID system with predictive analysis capabilities for brain cancer risk assessment. Key Requirements: - Predictive Analysis: Focus on risk assessment. - Data Source: Analyze medical imaging scans. Ideal Sk...predictive analysis capabilities for brain cancer risk assessment. Key Requirements: - Predictive Analysis: Focus on risk assessment. - Data Source: Analyze medical imaging scans. Ideal Skills & Experience: - Expertise in AI/ML, particularly in predictive analytics. - Experience with medical imaging data. - Background in healthcare technology is a plus. - Strong programming skills (Python, TensorFlow, etc.). - Ability to deliver secure and compliant health data solutions. Please provide relevant work samples and a...

...source files and outputs 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 s...

...what I need from you: Architecture & Data – Connect to major GDS and OTA APIs (Amadeus, Skyscanner, , etc.) and stream prices continuously. – Design a pipeline that normalises the data and feeds an ML model for deal scoring. – Implement efficient caching so agents always see fresh yet lightning-fast results. Deal Intelligence – Train or fine-tune a model (Python, scikit-learn/TensorFlow acceptable) that flags outlier bargains in real time and ranks them by savings, convenience and agent-defined preferences. – Expose this logic through a clean REST/GraphQL endpoint the front-end can hit on demand. Itinerary Engine – Given destination, dates and traveller profile, generate a structured day-by-day plan filled with top-rated attraction...

I need a developer who can take this idea from concept to a working, browser-based product. The core objective is to enrol users with a unique “vo...prompts prior to recording. Acceptance criteria • Enrolment and verification must run end-to-end in under five seconds on a typical broadband connection. • Equal Error Rate (EER) ≤ 5 % on a public speaker dataset or a comparable internal test set. • Clear documentation (setup, model training pipeline, API endpoints) plus a Dockerised deployment script. Tech stack is open, but Python (TensorFlow/PyTorch), Node.js, or Rust are all fine as long as you can justify the choice and meet the performance targets. Please outline your proposed approach, libraries you favour (Kaldi, SpeechBrain, etc.), and any simi...

...developer to help build AI-powered mobile applications. The work involves integrating machine learning models for real-time detection and analysis, both running locally on-device (offline) and via cloud APIs. Note: Your task will be integration of AI models in app architecture but its nice to have knowledge about AI models. What You'll Be Working On Integrating custom detection models (YOLO, TensorFlow Lite, ONNX) into Android apps Implementing on-device inference for offline functionality Connecting apps to AI APIs for cloud-based processing Optimizing model performance for android mobils(Snapdragon 6 cpus etc.) Building clean UI to display detection results in real-time Required Skills Strong Android development experience (Kotlin/Java/Flutter) Hands-on experience ...

...The core objective is simple: turn time-consuming manual work into an intelligent process that runs on its own. Because I don’t yet have data or legacy tools in place, we’ll define the workflow together, identify what information needs to be gathered, and then create the logic, models, or rule-based components that best fit. You’ll have full freedom to choose the right libraries—whether that’s TensorFlow, PyTorch, scikit-learn, spaCy, or a leaner approach using pure Python—so long as the end result is reliable, maintainable, and easy for me to extend later. Deliverables 1. Brief discovery call and written workflow outline 2. Prototype demonstrating successful end-to-end automation on sample data you create 3. Clean, well-commented Pytho...

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. The core ...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...

...market data. After I provide the raw market movements, the system should learn patterns and continuously refine its accuracy. Core deliverables: • Predict stock trends ahead of time • Analyze past market movements in an interactive timeline or chart view • Push real-time alerts the moment the model detects a significant event or deviation You are free to choose the most effective stack—TensorFlow or PyTorch for the model, and React Native, Flutter, or another proven framework for the apps—as long as the final build passes App Store and Google Play review. The AI must run efficiently server-side, expose a secure API to the app, and allow me to retrain or fine-tune the model with new data whenever needed. Please outline your proposed architec...

...probable numbers. The model must learn from three separate data streams—historical wheel outcomes, player betting behaviour logs, and detailed wheel-mechanics data—so it can pick up hidden biases and temporal patterns rather than relying on simple probability tables. Your task is to deliver a trained model plus everything I need to keep it learning as new data arrives. I’m comfortable with Python, TensorFlow/PyTorch, or a lightweight C++/C# inference library; whichever you choose, just expose a clean API that my front-end can call before each spin and return ranked predictions in well under 100 ms. Key deliverables: • End-to-end training pipeline (data cleaning, feature engineering, model training, validation) • Inference module or REST/gRPC serv...

...standalone report or dashboard, the assignment requires a fully realised project: working code, clear data-processing steps and concise documentation that I can present and defend. Here is what I need from you: • End-to-end pipeline: data sourcing or simulated dataset, cleaning and transformation, model training, evaluation and basic BI-style insights. • Well-commented Python or R notebooks (TensorFlow / PyTorch welcome) plus any auxiliary scripts. • A short explanatory document (≈5 pages) outlining objectives, methodology, results and how the solution fits within a Business Intelligence context. • Visual artefact: simple dashboard or set of plotted metrics that showcases key findings to a non-technical audience. Deep learning per visione artifi...

I need a lightweight application tha...that ties to the mood, tempo, or chord progression of the track. • Simple prompts where I can specify vibe, tempo, length, key, and a short theme to steer both music and words. • Export options: separate stems for vocals/instrumentals and a plain-text or SRT file of the lyrics. • A clean interface—CLI or desktop GUI is fine—as long as it works on Windows 10. I’m comfortable installing Python, TensorFlow, or similar AI frameworks if you prefer that route; otherwise a standalone executable is welcome. Source code ownership and a brief README covering dependencies and usage steps will be part of the hand-off. Once the program reliably produces coherent songs with synced lyrics and passes a quick originality check...

I have collected numerical manufacturing data and need a working large-language-model approach that can accurately predict our experimental outcomes so we can cut material waste on the shop floor. Here’s what I need from you: • Build and train the LLM-powered model entirely in Python (TensorFlow, PyTorch, or similar—whatever you prefer). • Use my numerical datasets as the sole training source; they cover typical manufacturing readings and KPIs. • Validate the model’s performance with clear metrics and a concise report that shows how well the predictions match real results. • Supply clean, well-commented code plus a brief read-me so my in-house engineers can rerun or fine-tune the model later. Acceptance is straightforward: when you...

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I need code writ...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.

...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 alternative open-source OCR engine if ...

...employable in Natural Language Processing. My goal is to understand core NLP concepts, build a small portfolio of projects, and feel confident discussing them in interviews. I already code a little in Python but have no formal NLP background. I’d like to cover the foundations—tokenisation, embeddings, transformers—then progress to hands-on mini-projects using libraries such as spaCy, Hugging Face, TensorFlow or PyTorch. Guidance on best practices for data preprocessing, model selection, evaluation and error analysis is essential, along with tips on how to present this work in a résumé or GitHub repo. Deliverables I have in mind: • A personalised learning roadmap with milestones • Live or recorded sessions focused on theory followed by...

...quality, and overall fit. Once I’ve tested your demo, I’ll outline the domain specifics and grant data access. The engagement will revolve around refining your existing model, exposing a clean REST or GraphQL API, and deploying the solution to my cloud environment (AWS or GCP). Solid accuracy, low latency, and well-documented Python code that leverages libraries such as Hugging Face, PyTorch, TensorFlow, or LangChain are all critical. Deliverables: • A publicly accessible link to your working NLP demo • Brief but clear architecture and tech-stack summary • A step-by-step plan to adapt the model to my use case • Final integrated solution with deployment and usage documentation I’ll review submissions on a rolling basis and follow up...

...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 scripts so I c...

I need a machine learning algorithm for a regression task using text data. Ideal Skills and Experience: - Proficiency in machine learning techniques, especially regression - Experience with text data processing and natural language processing (NLP) - Strong programming skills in Python or R - Familiarity with ML libraries like TensorFlow, Keras, or scikit-learn - Ability to preprocess, analyze, and model text data

I want to build a full, low-light-oriented NeRF pipeline whose sole goal is to lift image quality. The core of the work is on the model architecture itself; I am happy to keep pre- and post-processing simple as long as the neural radiance field you design excels in dim scenes. What I need from you: • A PyTorch (or JAX/TensorFlow if you strongly prefer) implementation of a NeRF variant tuned for low-illumination data. • Training and inference scripts that I can run on a single-GPU workstation. • A concise evaluation notebook that reports PSNR, SSIM and LPIPS on the validation set so I can judge improvements immediately. • Clear instructions on how to add new scenes or fine-tune further. The work is finished when I can clone the repo, point it at my datase...

...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 scripts so I c...

...switched on later; 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 ...

...computer-vision 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, • ...

...generate a clear voice-over, match it to dynamic visuals, and export a ready-to-publish HD file. Because the end goal is educational content, every output must be concise and concept-focused, using clean motion graphics rather than live-action footage. I’m open to whichever stack you feel fits—whether you build on top of tools like Stable Diffusion, RunwayML, Pika, Synthesia, or a custom Python/TensorFlow pipeline—as long as the final workflow is repeatable and easy for a non-technical user to operate. Key deliverables: • A working prototype that converts a supplied script into an animated explainer video. • Simple UI (web or desktop) allowing me to paste text, trigger rendering, and download the result. • Source code with brief setup notes so I...