Penglihatan Komputer Jobs

I need a reliable, camera-based solution that can automatically detect and count people captured by our existing CCTV network, regardless of whether the footage comes from indoor halls or outdoor entrances. The end goal is clear: turn those raw counts into actionable customer-analytics data I can slice by time, location, and traffic trend. Here’s what I’m expecting: • Accurate real-time or near-real-time counts from standard CCTV streams (no extra infrared hardware). • Robust performance under varying light and weather because some of our cameras sit outdoors. • An easy way for me to view and export daily, weekly, and monthly traffic reports—CSV download and a lightweight dashboard are perfect. • A straightforward deployment path: containerised code (...

I need a reliable pipeline that takes any pre-recorded video, swaps the on-screen face with a chosen target face, and keeps the lips perfectly synced to the original soundtrack. High accuracy is non-negotiable—phoneme-level alignment, natural mouth shapes, and seamless facial blending should hold up under close inspection and slow-motion playback. Preferred stack You’re free to combine proven solutions such as Wav2Lip, DeepFaceLab, FaceSwap, or custom GAN models, as long as the end result meets the visual standard. Python with PyTorch/TensorFlow is ideal because I want the option to retrain or fine-tune later, but an all-in-one executable is acceptable if thoroughly documented. Required deliverables • Use e.g. Kling AI, Wan 2.3 Runway ML Acceptance criteria •...

I’m looking for an experienced researcher–author to co-develop, write, and successfully submit a skin-disease–detection paper to a genuine, APC-free SCI-indexed journal and takes acceptance guarantee. Scope • Craft a manuscript that introduces and validates a brand-new detection algorithm. • Build experiments around whichever deep-learning model is currently most promising—CNN, transformer, hybrid, or any other trending architecture—so long as the results outperform or clearly benchmark against existing methods. • Handle all stages from dataset curation, model training, result analysis, and figure/table preparation through to journal formatting, cover letter, and submission. • Guide the paper through peer review until acceptance. ...

Project Overview: We are building a data analysis platform and require a Computer Vision / Digital Signal Processing expert to implement a server-side automated motion analysis engine. The frontend application layer is already complete and successfully uploads a cropped "eye-strip" video (focusing strictly on the eye region) directly to our server backend. Your Task: you will leverage existing open-source frameworks (such as OpenCV contour tracking, MediaPipe Iris, or similar established eye-tracking libraries) to build a highly reliable server-side script (Python preferred). This script must trigger automatically upon video upload to process the cropped video frame-by-frame. Core Technical Deliverables: 1. Object Tracking & Noise Filtering: Utilize MediaPipe Iris or OpenCV...

We are developing a drone-to-drone vision system using a Raspberry Pi 5 and a 40 TOPS AI Accelerator. The system must: Detect another drone using the camera feed Track the detected drone in real time Generate guidance commands to keep the target centered in view Support autonomous follow behavior Preprocess camera images for AI inference Train and optimize object detection models Optimize performance for low latency and high FPS on Raspberry Pi Required Skills: Python OpenCV YOLO/Object Detection Object Tracking (ByteTrack, DeepSORT, etc.) Raspberry Pi Edge AI Deployment Drone Systems and Navigation Preferred Experience: Drone vision projects Autonomous tracking systems Real-time AI inference on embedded devices Raspberry Pi AI accelerator deployment This is a guidance and developme...

A new cross-disciplinary build is about to start, combining solid software engineering with practical artificial-intelligence features. The first milestone centres on scoping: together we will decide whether the core product emerges as a web, mobile or desktop application and lock down the primary language stack—Python, JavaScript, Java or a hybrid approach. From there, the work shifts to architecture design, clean code implementation, and the integration of an AI component that demonstrably adds value (machine-learning, NLP, or computer-vision models will be chosen once use-cases are finalised). Version control through Git, test coverage, and concise technical documentation are expected throughout the sprint. The immediate deliverable is a working proof of concept that showcases a...

I have a collection of images featuring plates that contain both numbers and alphabet characters. The plates are already labeled, but I need each annotation carefully validated and, whenever necessary, corrected. Your task is to open every image, check that the plate region truly matches the ground-truth label, and fix any inaccuracies you see so the dataset is production-ready. Accuracy is absolutely critical here—if a bounding box is off by even a few pixels or if a character has been mis-read, the file must be updated. I would like the final result to be a clean set of corrected annotation files (JSON or XML, whichever you prefer) plus the revised images, zipped and ready for model training. A brief change log noting the number of fixes you made will also help me keep track of ov...

I have a complete OCT (optical coherence tomography) image set and now need to turn it into a full, publication-ready study on age-related macular degeneration (AMD). The work has to run entirely in Google Colab and revolve around a hybrid deep-learning architecture of your choice—CNN + transformer, ensemble CNNs, or any comparable combination—as long as it meets strong SCI journal standards. Pre-processing Both FFT and Wavelet Transform must be applied. Please document each step in the notebook so the signal-processing pipeline is clear and reproducible. Core modelling • Train, validate and test the model on the OCT data. • Track and store all metrics so they can be plotted later. • Incorporate Explainable AI focused on feature-importance visualisation...

I have a single 40-second MP4 clip that shows two motorcycles circulating the same track. Each bike can be separated at a glance because they are painted different colours. What I need is a reliable, frame-accurate measurement of the time interval between the first and the second motorcycle as they pass a chosen reference line on the circuit. Please use YOLO (or an equivalent real-time object detector) to: • detect both bikes throughout the whole sequence, • define a consistent reference line or region on the track, • timestamp the exact moment each bike crosses that reference, and • burn a clear visual overlay onto the video that displays the calculated gap in seconds. The finished deliverable is the processed video with the overlay already embedded; no separa...

I am in the middle of my master’s thesis and need a capable partner to handle the coding side of a deep-learning project on mammogram images. The core task is to build a robust model for breast-cancer diagnosis; once the network architecture is in place I can take care of statistical write-ups and broader discussion, but I need you to get the codebase production-ready and well-documented. Here’s what the collaboration will look like: • Data: I will supply the curated mammography dataset and any preprocessing scripts I have so far. • Model building: Using Python with either TensorFlow or PyTorch (whichever you work fastest with), you will design, train and fine-tune a CNN or transformer-based pipeline that targets breast-cancer detection specifically. • Resu...

I need to turn a Large Language Model into a practical, real-time assistant that runs directly on an NVIDIA Jetson board. The model will reason over image data at the edge, so every millisecond saved and every megabyte spared matters. Memory-optimised execution is therefore the single most important constraint, though I still expect you to keep latency low and power draw sensible. Here is what I want to achieve. The LLM must accept a pre-processed visual input, apply prompt-engineering tricks that preserve context, and reply fast enough to be useful on-device—no cloud fallback. Smart caching, selective quantisation, and, when it genuinely pays off, lightweight fine-tuning are all on the table. I will look to you to suggest the right mix of techniques and to implement them. You shou...

I need a lean, working proof-of-concept that automatically counts foot traffic using a single 360-degree camera. The goal is to drop the unit into busy conference halls, festival entrances, or outdoor promotional zones and have it return reliable head-counts without manual intervention. Here is what matters to me: • Vision logic: Please build or integrate computer-vision models (OpenCV, YOLO, TensorFlow Lite or similar) that detect and track people moving through the camera’s full 360° field of view. The algorithm must distinguish unique passes so that every person is counted once. • Edge or cloud flexibility: I am fine with the model running on a Raspberry Pi 4, Jetson Nano, or a small cloud instance—as long as latency is low and setup remains simple. • ...

We are Sprectex AI, a growing artificial intelligence company specializing in Computer Vision, AI automation, and enterprise-level AI solutions. We have a strong team of 50+ AI engineers and specialists across different regions, actively working on real-world deployments and client projects. Our focus is on building scalable, production-ready AI systems for global clients. We already have multiple working AI systems deployed with real clients, and we are now expanding our operations into the US market. We are currently looking for a serious and experienced US-based Business Development Partner / Sales Representative who can help us generate leads, connect with enterprise clients, and close high-value deals. The ideal candidate will be responsible for identifying potential clients, buil...

I have a complete OCT (optical coherence tomography) image set and now need to turn it into a full, publication-ready study on age-related macular degeneration (AMD). The work has to run entirely in Google Colab and revolve around a hybrid deep-learning architecture of your choice—CNN + transformer, ensemble CNNs, or any comparable combination—as long as it meets strong SCI journal standards. Pre-processing Both FFT and Wavelet Transform must be applied. Please document each step in the notebook so the signal-processing pipeline is clear and reproducible. Core modelling • Train, validate and test the model on the OCT data. • Track and store all metrics so they can be plotted later. • Incorporate Explainable AI focused on feature-importance visualisation...

I’m adding an end-to-end virtual fitting room to my e-commerce site so visitors can upload a full-body photo and immediately see our apparel draped on their own figure—accurate pose, lighting, and cloth dynamics included. The workflow I have in mind combines human-parsing, garment warping, and a lightweight generative model that streams results straight to the browser. Core features I need implemented: • Real-time try-on with latency low enough to feel instant • Save & share so customers can download a composite or post directly to social platforms • Size recommendations that read body proportions from the uploaded image and match them to our inventory’s size chart I’ll provide product photography and size tables; you’ll build the co...

I need a complete Python pipeline that ingests CCTV streams from several in-store cameras and turns them into actionable retail metrics. Using YOLOv8 for detection, ByteTracker plus a solid Re-ID module for cross-camera identity preservation, the system must • detect and track people only (no vehicles, animals, etc.) • avoid double-counting the same shopper when they move between overlapping views • distinguish staff from shoppers so employees are never included in customer statistics • produce reliable foot-traffic counts, crowd-density heatmaps and an “entry-to-purchase” conversion figure (how many visitors become paying customers) Please deliver: 1. Well-structured, documented Python code (YOLOv8 + ByteTracker + ReID) that runs on recorded f...

I’m about to start a complete pool remodel and I want an AI-powered visual diary that lets me see, day by day, how the work is progressing. Each morning I’ll upload photos, short clips, delivery notes and any site drawings; by the evening I expect an updated, time-stamped visualization that overlays the latest data onto the existing 3-D scene so I can instantly understand: • Structural changes that were cut, poured, drilled or installed • How much of each material has actually gone in versus my specification • Where the crew was active and for how long, flagged on the model Because I need this information daily, the workflow has to be largely automated—computer-vision photo alignment, AI segmentation for materials, and an engine such as Blender, Unr...

Busco a un/a especialista con experiencia comprobable en Intel RealSense SDK para impartir una sesión virtual de 4 horas a cinco instructores técnicos de una institución educativa pública. Contexto • Perfil del grupo: Principiante en la tecnología Intel RealSense. • Plataforma disponible: Computadora con Windows para cada participante. • Fecha: a coordinar durante junio 2026. • Idioma de la sesión: español. Temario deseado 1. Instalación y configuración inicial del sensor D455 y del SDK. 2. Captura de imágenes y videos en tiempo real. 3. Análisis de datos básicos (depth, point cloud). 4. Ejemplos de aplicaciones educativas y de prototipado rápido con la cá...

Мне нужен специалист, который настроит и обучит кастомный AI-модуль, а затем возьмёт на себя его дальнейшее обслуживание. Главная цель — автоматизировать рутинные процессы. Что именно нужно автоматизировать • Обработку данных: быстрая сортировка, очистка, классификация и извлечение структурированной информации. • Управление проектами: автоматическое составление отчётов, контроль сроков, распределение задач. • Маркетинг: генерация контента, анализ кампаний, сегментация аудитории. Типы данных для работы Мы даём на вход три вида данных, поэтому модель должна уверенно справляться как с NLP, так и с компьютерным зрением и табличной аналитикой: • Тексты и документы (NLP). • Изображения и видео (CV). • Числовые данные и таблицы (ETL, ML). Жела...

I'm seeking an experienced software engineer to develop a control system with functionalities for object detection and tracking. The project will utilize both Python and OpenCV. Key Requirements: - Develop a control system - Implement object detection and tracking functionalities - Use Python and OpenCV Ideal Skills and Experience: - Proficiency in Python and OpenCV - Experience in control system design - Strong background in computer vision techniques - Problem-solving skills and attention to detail Please provide examples of similar projects completed and a brief outline of your approach.