Tapy Video annotation.
The quality measure was that it should be annotated with 80% correction.
Hire this AI Trainer
Sign in or create an account to invite AI Trainers to your job.
No subject matter listed
Executive Summary We provide high-precision data annotation services to power advanced Computer Vision and Generative AI models. Our team delivers the pixel-perfect, highly accurate training data required for production-ready machine learning. We manage the entire pipeline—from guidelines setup to final quality delivery—so your engineering team can focus strictly on model development. Core Annotation Services 1. Video Annotation & Object Detection We specialise in high-density video labelling with a strict focus on temporal tracking and frame-to-frame continuity. Autonomous Driving & ADAS: Expert mapping of complex road environments. Dynamic Object Tracking: Consistent ID tracking for Pedestrians, Cyclists, and multi-class Vehicles across moving frames. Infrastructure Mapping: Precision labelling of Drivable Roads, Sidewalks, Crosswalks, and Lane Lines (Solid, Dashed, Double) using bounding boxes and polylines. Traffic Elements: Detection of Traffic Lights, Road Signs, and Painted Road Arrows. 2. Image Annotation & Segmentation We deliver granular spatial data for static image datasets. Bounding Boxes & Polygons: Tight, error-free framing for exact object localisation. Semantic & Instance Segmentation: Pixel-level classification to separate overlapping objects from complex backgrounds. 3. GenAI Response Evaluation We manage human-in-the-loop pipelines to optimise and align Large Language Models (LLMs). RLHF Pipelines: Evaluating AI outputs for accuracy, safety, policy compliance, and helpfulness. Multimodal Evaluation: Reviewing models that combine text, image, and video data. Our Quality Assurance & Project Workflow Phase 1: Taxonomy & Guidelines: We translate your raw project requirements into strict, edge-case-proof labelling manuals. Phase 2: Pilot & Calibration: We run a small-batch pilot to align annotator performance with your exact expectations. Phase 3: Production & Multi-Stage QA: Every dataset undergoes automated syntax checks and human spot-checking to maximise accuracy. Phase 4: Secure Delivery: Final data is exported securely in your preferred format (JSON, XML, COCO, YOLO, etc.).
We value security as per the client's needs, and we follow that.
The quality measure was that it should be annotated with 80% correction.