Osman Harun

Key Skills

Software

CVAT

Encord

Labelbox

Roboflow

SuperAnnotate

Supervisely

V7 Labs

Top Subject Matter

No subject matter listed

Top Data Types

Audio

Image

Text

Video

Top Label Types

Bounding Box

Classification

Cuboid

Data Collection

Object Detection

Point Key Point

Polygon

Polyline

Segmentation

Freelancer Overview

I am an experienced data annotation team leader and AI research specialist with a strong background in managing high-quality data labeling projects. My expertise includes overseeing annotation teams, ensuring data accuracy, and implementing workflow optimizations to deliver reliable training data for AI models. I have hands-on experience with generative AI tools for image and video creation, as well as conducting deep web research and competitor analysis to support data-driven decision-making. My skills in AutoCAD 2D/3D, Microsoft Office, and digital content generation allow me to bridge technical and operational requirements, while my focus on data security and team training ensures project success in fast-paced environments. I am fluent in both English and Bangla, and thrive in collaborative settings where precise, efficient data handling is critical.

Labeling Experience

Horse Race Annotation

CVATImagePolygon

This project involved polygon image annotation for a computer vision dataset related to horse racing. I segmented horses by carefully drawing polygon boundaries around each horse to separate the animal from the background. The work required identifying fast-moving subjects, handling motion blur, occlusion, and different camera angles while maintaining accurate edge alignment. All annotations were completed according to project guidelines to ensure consistency and high-quality training data for AI models.

This project involved polygon image annotation for a computer vision dataset related to horse racing. I segmented horses by carefully drawing polygon boundaries around each horse to separate the animal from the background. The work required identifying fast-moving subjects, handling motion blur, occlusion, and different camera angles while maintaining accurate edge alignment. All annotations were completed according to project guidelines to ensure consistency and high-quality training data for AI models.

2025 - 2025

Car Segmentation

CVATImagePolygon

This project involved image segmentation and polygon annotation for a computer vision dataset focused on vehicles. I annotated cars by carefully drawing polygon boundaries around each vehicle to accurately separate the object from the background. The task required identifying different car shapes, handling occlusions, and maintaining precise edge alignment across various lighting conditions and camera angles. All annotations were completed following project guidelines to ensure consistency and dataset accuracy for AI model training.

This project involved image segmentation and polygon annotation for a computer vision dataset focused on vehicles. I annotated cars by carefully drawing polygon boundaries around each vehicle to accurately separate the object from the background. The task required identifying different car shapes, handling occlusions, and maintaining precise edge alignment across various lighting conditions and camera angles. All annotations were completed following project guidelines to ensure consistency and dataset accuracy for AI model training.

2025 - 2025

Horse Annotation

CVATImageBounding BoxPoint Key Point

This project involved key-point image annotation for a computer vision dataset related to horse pose estimation. I labeled 51 anatomical landmark points on each horse image, including joints, limbs, hooves, back, and body connection areas. The work required accurately identifying visible body parts, handling different poses and camera angles, and following strict annotation guidelines. Quality control was maintained by ensuring precise and consistent placement of each point, and hidden parts were not annotated according to the instructions.

This project involved key-point image annotation for a computer vision dataset related to horse pose estimation. I labeled 51 anatomical landmark points on each horse image, including joints, limbs, hooves, back, and body connection areas. The work required accurately identifying visible body parts, handling different poses and camera angles, and following strict annotation guidelines. Quality control was maintained by ensuring precise and consistent placement of each point, and hidden parts were not annotated according to the instructions.

2025 - 2025

Data Annotation Team Leader

LabelboxImageClassification

Led a team responsible for data annotation tasks in various AI projects. Ensured high-quality, accurate annotations were completed on schedule while training and guiding annotators. Conducted regular quality checks and workflow improvements for optimal results. • Coordinated annotation task assignments • Maintained data security and compliance • Supervised annotation reviews and feedback • Streamlined annotation methodologies

Led a team responsible for data annotation tasks in various AI projects. Ensured high-quality, accurate annotations were completed on schedule while training and guiding annotators. Conducted regular quality checks and workflow improvements for optimal results. • Coordinated annotation task assignments • Maintained data security and compliance • Supervised annotation reviews and feedback • Streamlined annotation methodologies

2022 - 2024

Education

Work History