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Writing EyeQ is a futuristic AI-powered visual intelligence mobile application for iOS and Android. The app allows users to point their camera at anything in the real world and instantly receive AI-powered explanations, diagnostics, safety warnings, repair guidance, educational information, estimated costs, and local professional recommendations. We are looking for experienced developers or a development team with strong backgrounds in: • AI application development • Computer vision / image recognition • Mobile app development (iOS + Android) • AI API integration • Cloud backend systems • UI/UX design for modern futuristic apps • Real-time image processing • Subscription/payment systems • Location/GPS integration • Database architecture and...

Quiero sacar el máximo partido al kit Grove Vision AI v2 unido a un microcontrolador XIAO para ejecutar reconocimiento facial directamente en el borde. El sistema debe funcionar al aire libre, en plena naturaleza, de modo que la latencia sea mínima y no dependa de la nube. Ademas el dispositivo al reconocer en el entorno natural debe ser capaz de enviar la información en tiempo real ya sea a una pagina web o dispositivo movil, tambien debe ser capaz de generar imformes con los datos recopilados. Cuento con un conjunto de imágenes de fauna silvestre que servirá como dataset de entrenamiento; necesito tu ayuda para limpiar ese material, entrenar el modelo y convertirlo al formato óptimo para el Grove Vision AI v2, asegurando que corra con la memoria...

## AI Shuttle Speed Predictor — Freelancer Project Description I am looking for a skilled AI/Computer Vision developer to build an **AI-powered Badminton Shuttle Speed Predictor App** capable of analyzing badminton videos and predicting shuttle speed using computer vision and machine learning techniques. The application should process uploaded or live-recorded badminton videos, track shuttle movement frame-by-frame, calculate shuttle speed, and display analytics through an interactive dashboard. ### Core Features Required * Video upload and processing * Real-time shuttle detection and tracking * AI/computer vision integration using OpenCV and YOLO * Shuttle speed prediction in km/h and m/s * Shot trajectory visualization * Speed analytics dashboard * Match and rally analysis * Hi...

I'm seeking a tutor for computational image processing and data-driven methods (machine/deep learning), specifically for my biomedical engineering coursework. I'm looking for assistance in: - Image segmentation - Feature extraction - Image registration - Binary images - Image transforms The exam is mathematical and theoretical. Ideal skills and experience: - Expertise in computational image processing - Proficiency in data analysis, visualization, and statistical methods - Excellent teaching and communication skills Looking forward to your expertise!

We are looking for a hands-on Senior Computer Vision Architect to scale our live multi-camera video analytics platform from 100 to 1,000+ cameras across NVIDIA DeepStream and distributed edge device architectures. The ideal candidate must have strong production experience with NVIDIA DeepStream SDK, TensorRT optimization, edge AI deployments, and large-scale camera infrastructure. Responsibilities: • Design and manage a scalable 1,000-camera architecture with high availability and low latency • Optimize DeepStream pipelines (NvInfer, NvTracker, NVDEC, GStreamer) for stable FPS under heavy load • Deploy an manage CV models on Jetson or equivalent edge devices • Fine-tune YOLO models and export optimized TensorRT engines • Build and improve infrastructure using Doc...

I’m building Face2Tune, a web app that watches a user’s webcam feed, recognises when they look Happy, and instantly queues up music that matches that vibe. The front-end is React; the back-end is a small Node.js / API. Computer-vision runs in the browser so latency stays low, and I’ll store nothing on the server except the track catalogue. Here’s what I need from you: • Integrate a reliable browser-side emotion-detection model (only the Happy class is required for now, but the code should be easy to extend for Sad or Angry later). • When “Happy” is detected, fetch a curated playlist from the back-end and display it in the UI. • Add a simple toggle that lets the user manually choose their mood instead of relying on the camera. &bul...

I am looking for an experienced Computer Vision Engineer to build a robust c++ script that automatically detects and maps the scoring rings on a B27 shooting target from standard smartphone photos. "i want it in c++" The End Goal: Given a photo of a used B27 shooting target (taken at various angles and lighting conditions), the script must automatically correct the perspective, locate the target, and accurately identify/draw the scoring rings (X, 10, 9, 8, 7) so that bullet impacts can eventually be scored. The Challenges (Why this isn't a basic OpenCV tutorial): Bullet Holes: The paper is covered in bullet holes. Traditional edge detection (like finding the white rings using Canny/Hough) often fails because the bullet holes destroy the lines. Perspective Distortion: Photos ...

I’m putting together a fully-featured, production-ready web application that will inspect injection-moulded plastic parts in real time by analysing a live camera feed through a Vision API. The system must run on a Windows machine yet be accessible from any browser via a clean, responsive dashboard. Core workflow The application will capture each part as it comes off the moulding machine, push the image frames to the Vision API, and instantly decide pass / fail according to defect thresholds I can configure on-screen. Every inspection, result, and high-resolution frame should be logged so I can audit trends or trace specific batches later. Operator dashboard I want a web-based dashboard that: • Streams the live camera view with colour-coded status (pass, fail, uncertain...

I am building a research-grade pipeline that focuses first and foremost on Diabetic Retinopathy (DR) grading, while keeping an eye on downstream extensions such as DME detection, retinal biomarker discovery, longitudinal modelling, cross-dataset generalisation and explainable retinal AI. Data at hand • Thousands of colour fundus photographs sourced from OLIVES, MMRDR and my own curated set. • Structured patient medical history accompanying a subset of those images. Core objectives 1. Train and validate a model that assigns the correct severity level to every DR image. 2. Surface early-stage indicators that could alert clinicians before conventional thresholds are reached. 3. Provide per-patient progression tracking so that sequential visits can be plotted and foreca...

I need a software solution that uses machine learning to assess apple quality, bruising, and diseases through images. The software should be compatible with either Windows and MacOS, and images will be uploaded via a camera interface. Key Requirements: - Machine learning integration for advanced image analysis - User-friendly camera interface for image capture Ideal Skills and Experience: - Expertise in machine learning and image processing - Experience in developing cross-platform software applications - Strong background in computer vision Please provide samples of previous work in similar domains.

I want to put together a quick-and-dirty paper prototype that proves one thing: textual instructions can be fed into an LLM, interpreted, and turned into accurate anatomical motion that I can later visualise in my copilot 3d js etc. The workflow I have in mind is simple on paper yet technically layered. First, the LLM receives short, structured cues (“Raise left arm to 90°”, “Rotate torso 15° right”, etc.). It must parse those sentences, identify the key actions, and output a sequence of joint-level positions. From there, the prototype should pass those positions to a lightweight Vision-AI / pose-estimation module so I can preview the motion as stick-figure frames and sanity-check anatomical correctness. Because this is an early prototype, I’m not ask...

I have a growing library of MP4 recordings of casino-grade slot machines and I need a reliable way to turn each session into structured data. For every spin I want the script to capture the start time, end time, bet size, win amount, any bonus triggers, and jackpots, then tally an overall spin count. The videos cover many different games, so the screen layout shifts from title to title; your solution therefore has to locate each region of interest on its own instead of relying on hard-coded coordinates. Because bonuses and jackpots are marked with visually distinct graphics, you can leverage that cue when classifying events. Accuracy matters more than raw speed, but I still expect processing to run unattended once configured. Please build a computer-vision / OCR pipeline that: • Au...

I aim to build an advanced, research-grade Virtual Try-On (VTON) engine that can realistically place Tops (e.g., shirts, blouses), Bottoms (e.g., pants, skirts), and Full outfits (e.g., dresses, suits) onto a human model from nothing more than a single 2-D photograph. The workflow should centre on state-of-the-art deep generative techniques—diffusion models, flow-matching, and transformer-based architectures—so the final renders look genuinely photo-realistic, preserve garment texture, and respect body pose and occlusion. The system will be trained on a curated dataset I already possess, then fine-tuned to accept JPEG and PNG uploads at inference time. Clean, modular PyTorch (or equivalent) code, a reproducible training pipeline, and inference scripts that run on a single high...

# Senior Android AR Indoor Navigation Developer (CameraX + Sensor Fusion + AR) We are building an advanced Android AR Indoor Navigation App for malls and large indoor spaces. The app combines: * AR navigation * Indoor localization * Landmark/logo detection * Sensor fusion * Real-time navigation * Dead reckoning * Graph-based routing ## Project Overview The application uses the smartphone camera to detect indoor landmarks/logos and estimate the user's position inside a mall using computer vision and graph-constrained localization. The system then provides: * AR navigation overlays * Indoor map navigation * Real-time rerouting * Continuous tracking ## Core Features ### Localization Pipeline * CameraX live camera preview * Multi-landmark/logo detection * Embeddings database mat...

I have a collection of general-purpose images and need a complete Python-based pipeline that extracts meaningful features and classifies each image accurately. The project centres on image feature extraction and subsequent classification, so solid experience with OpenCV, scikit-learn or a deep-learning stack such as TensorFlow or PyTorch is essential. You will begin by deciding on (and justifying) an appropriate feature strategy—traditional descriptors like SIFT/ORB, transfer-learning from a CNN, or another proven method—then train and validate a classifier that reaches reliable accuracy on a held-out test set. Clean, well-commented code and clear, reproducible training steps are critical because I need to retrain the model as new data arrives. Deliverables • Python sour...

我准备上线一套面向居家场景的智能监测系统，希望通过视觉与物联网技术，及早发现老人或慢病人群的高危状况并推送告警。 核心需求 1. 高危动作异常 —— 同时精准识别“摔倒”与“跌倒”，第一时间触发报警。 2. 状态失能异常 —— 既要判断“长时间静止不动”，也要捕捉“无自主行为”状态，实现持续跟踪。 3. 出入与行为节律 —— 对家门进出时间、频次和时段进行建模，结合如厕频率、徘徊轨迹、家电使用等行为模式，挖掘偏离日常规律的征兆。 4. 生理体征 —— 基于微动信号提取呼吸、心率等指标，与个人基线比较后给出健康风险提示。 我期望的交付 • 场景与传感器选型报告：摄像头、毫米波雷达、惯性传感器等可行性分析。 • 算法与模型：包含数据清洗、特征工程、深度学习或传统 CV/信号处理方案，需给出训练脚本与推理 API。 • 功能性原型：可在本地或边缘端实时运行，界面展示告警信息，并通过 MQTT/HTTP 推送到后台。 • 技术文档：部署指南、接口说明、测试用例及关键性能指标（例如跌倒检测准确率、误报率等）。 理想人选 熟悉 OpenCV、PyTorch/TensorFlow 或 mmWave SDK，对人体姿态估计、时序异常检测有实战经验；能在 Linux + Docker 环境里快速迭代；对养老、康复或智慧家居项目有交付记录更佳。 请附上相关案例、模型效果或仓库链接，让我能快速评估你的解决思路和交付能力。期待与你合作，把这套居家安全“护身符”尽快落地。

我正在搭建一套基于 YOLOv8 的垃圾分类演示，需要完整的软硬件方案： • 软 件 – 使用 Python + YOLOv8 训练/部署模型，能在普通电脑上直接运行； – 摄像头以 USB 方式接入树莓派，再把画面实时传输到电脑； – 识别目标包含：塑料、纸张以及易拉罐，模型应能在画面上框出目标并同时在终端输出中文文字描述（如“检测到易拉罐”）； – 运行界面可为简单命令行或轻量 GUI，只要识别结果与文字描述同步显示即可； – 提供完整的源代码、模型权重、依赖清单与一键安装脚本。 • 硬 件 – 树莓派主板（任意 3/4/5 型号均可）+ 原厂摄像头模块； – 摄像头默认 USB 连接，可在本地测试无误后将整套硬件打包寄送给我（运费我承担）。 • 交付要求 1. 远程演示识别过程，确认三类垃圾均能被准确框选并输出文字； 2. 打包代码与文档（环境配置、使用说明、模型训练思路）； 3. 寄送硬件并提供收件追踪号； 4. 收到设备后，如有环境差异需协助我本地跑通。 如果你熟悉树莓派、YOLOv8 和 Python 部署，并具备打包邮寄能力，期待与你合作！

I am looking for an expert to develop a high-performance, 8-channel automated farming system for the 3D tactical shooter Delta Force. My requirements: Technical Skills & Experience: - Proven experience in real-time computer vision (YOLO, TensorRT) with batch inference and low latency on RTX 4070Ti/4060Ti GPUs. - Strong proficiency in C++ (or high-performance Python with CUDA/C++ backend) and PCIe capture card integration. - Familiarity with KMBOX Net HID-level mouse/touch emulation and anti-cheat evasion (Tencent ACE or similar). - Experience designing centralized dashboards and robust fail-safe management for 24/7 operations. Core Deliverables: - Real-time detection (loot, enemies, extraction points) and UI state recognition via 8x 1080p 60Hz streams. - Visual navigation using only...

I have a curated set of roughly 700 post-operative periapical X-rays taken after root canal treatments by dental students. I need a computer-vision model, built in Python with TensorFlow or PyTorch, that can automatically assess each case and return two outputs: • a numeric score that can be used in our grading spreadsheet, and • a concise feedback report highlighting strengths and mistakes. The evaluation must cover the accuracy of the root-canal pathway, cleanliness of the treated area, and overall completion quality. I will provide a detailed rubric with additional sub-criteria so the model can translate radiographic findings into tutor-style comments. Your job is to design, train, and validate the model, then package an inference script that accepts a single X-ray or...

We are hiring highly skilled professionals to evaluate AI-generated artifacts for a large-scale AI quality initiative known as “Project Hawk.” This is NOT traditional software development work. The role focuses on evaluating the quality, usability, visual polish, structure, and editability of AI-generated outputs across multiple domains including: * software engineering artifacts * UI/UX and design systems * presentation materials * spreadsheets and documents * multimodal and computer vision outputs Compensation: • Approx. $75/hour • Flexible task-based work • High performers may scale to substantial weekly earnings depending on task availability and quality Open Specializations: 1. Software Engineering Evaluators 2. UX/UI & Visual Design Evaluators 3. ...

I run a highly successful U.S.-based IT staffing firm that has flourished since 2000, and it is time for us to add a robust, agent-centric AI/ML capability across the organisation. I need an expert who can design and deliver an online, intensive programme that upskills our current employees and future employees in three core domains—Python, machine-learning algorithms, natural-language processing, and computer vision. Most importanty enable them to become powerful Agentic Developer or Lead Agnetic Developers—while introducing the latest agentic development patterns that tie them all together. Here is what I am looking for: • A practitioner-level curriculum that moves quickly from fundamentals to production-grade agent frameworks (think LangChain-style tool orchestration...