Durgaa Patnala

Key Skills

Software

AWS SageMaker

Anno-Mage

Appen

Argilla

Axiom AI

Clickworker

CloudFactory

CrowdFlower

CrowdSource

CVAT

Data Annotation Tech

Dataloop

Datatroniq

Datumbox

Datasaur

Datature

Dataturk

Deep Systems

Diffgram

Doccano

Encord

Figure Eight

Google Cloud Vertex AI

Hasty

HiveMind

Humanatic

iMerit

Img Lab

Kili Technology

Labelbox

LabelImg

Label Studio

LightTag

Lionbridge

Mercor

Mighty AI

Mindrift

OneForma

OpenCV AI Kit (OAK)

Playment

Prodigy

Redbrick AI

Remotasks

Roboflow

Sama

Scale AI

Sloth

Snorkel AI

SuperAnnotate

Supervisely

Surge AI

Tagtog

Toloka

Telus

Trilldata Technologies

VoTT

V7 Labs

Other

Internal/Proprietary Tooling

Top Subject Matter

No subject matter listed

Top Data Types

Document

Image

Text

Top Task Types

Bounding Box

Classification

Polygon

Polyline

Segmentation

Freelancer Overview

With strong expertise in AI training data and computer vision annotation, I have worked on a wide range of data labeling, document automation, and text processing projects. My experience covers 2D and 3D image annotation, LiDAR point cloud labeling, and OCR-based document extraction for industries such as automotive, healthcare, finance, and e-learning. I’m proficient with leading tools like CVAT, Labelbox, Roboflow, and Supervisely, ensuring accuracy, consistency, and scalability in every dataset. In addition to annotation, I specialize in AI-assisted document automation, transforming unstructured data into structured, machine-readable formats. I have contributed to LLM dataset preparation, multilingual text labeling (English, Spanish, Telugu), and workflow optimization for high-volume projects. My focus is always on quality, efficiency, and innovation, helping clients accelerate their AI and automation goals through reliable and well-structured data.

Labeling Experience

Experience in CVAT – Architectural Floor Plan Map Annotation

CVATImageBounding Box

I have experience working on CVAT (Computer Vision Annotation Tool) to annotate architectural floor map diagrams. My tasks included creating bounding box annotations for various structural components such as rooms, doors, halls, walls, and other floor layout elements. I ensured clear, accurate, and consistent labeling to support high-quality dataset generation for floor plan detection and analysis models.

I have experience working on CVAT (Computer Vision Annotation Tool) to annotate architectural floor map diagrams. My tasks included creating bounding box annotations for various structural components such as rooms, doors, halls, walls, and other floor layout elements. I ensured clear, accurate, and consistent labeling to support high-quality dataset generation for floor plan detection and analysis models.

2025 - 2025

Roboflow Annotation Experience (Security Camera Images)

RoboflowImageBounding BoxPolygon

I worked on Roboflow for data annotation tasks, where I processed images captured from security surveillance cameras. I performed annotations using bounding boxes and polygon-based segmentation to achieve precise labeling of objects. I ensured data quality, consistency, and accuracy to support object detection and computer vision model training.

I worked on Roboflow for data annotation tasks, where I processed images captured from security surveillance cameras. I performed annotations using bounding boxes and polygon-based segmentation to achieve precise labeling of objects. I ensured data quality, consistency, and accuracy to support object detection and computer vision model training.

2025 - 2025

Button and UI Element Labeling

RoboflowImageBounding BoxPolygon

Annotated over 2,500 catalog images containing multiple buttons and icons. Used bounding boxes and polygons to label UI elements at various angles and inclinations. Followed strict QA checks with double-review for precision and consistency across batches.

Annotated over 2,500 catalog images containing multiple buttons and icons. Used bounding boxes and polygons to label UI elements at various angles and inclinations. Followed strict QA checks with double-review for precision and consistency across batches.

2025 - 2025

Autonomous Vehicle Image, Bounding Box, Polygon & LiDAR Annotation

CVATImageBounding BoxPolygon

Worked on large-scale 2D and 3D image annotation and LiDAR point cloud labeling for an autonomous vehicle dataset. The project involved identifying vehicles, pedestrians, lane markings, and traffic signs using tools such as CVAT and SuperAnnotate. Maintained high annotation accuracy and consistent labeling quality through a multi-stage QA process. Responsibilities: Annotated bounding boxes, polygons, and keypoints across diverse environmental conditions (day/night, rain, city, highway). Handled LiDAR point cloud labeling for object detection and depth segmentation. Collaborated with QA and automation teams to ensure 98%+ data accuracy and model-ready outputs. Optimized labeling workflows for faster turnaround using tool-based shortcuts and AI-assisted techniques. Skills & Tools Used: CVAT, Supervisely, Labelbox, Roboflow, QA Review, Computer Vision, 2D/3D Labeling, LiDAR Annotation Outcome: Successfully delivered 50,000+ annotated frames used for training object detection and

Worked on large-scale 2D and 3D image annotation and LiDAR point cloud labeling for an autonomous vehicle dataset. The project involved identifying vehicles, pedestrians, lane markings, and traffic signs using tools such as CVAT and SuperAnnotate. Maintained high annotation accuracy and consistent labeling quality through a multi-stage QA process. Responsibilities: Annotated bounding boxes, polygons, and keypoints across diverse environmental conditions (day/night, rain, city, highway). Handled LiDAR point cloud labeling for object detection and depth segmentation. Collaborated with QA and automation teams to ensure 98%+ data accuracy and model-ready outputs. Optimized labeling workflows for faster turnaround using tool-based shortcuts and AI-assisted techniques. Skills & Tools Used: CVAT, Supervisely, Labelbox, Roboflow, QA Review, Computer Vision, 2D/3D Labeling, LiDAR Annotation Outcome: Successfully delivered 50,000+ annotated frames used for training object detection and

2024 - 2025

Financial Conversation Data Annotation

V7 LabsTextEntity Ner Classification

Annotated a financial AI advisor dataset including intent classification, transaction and merchant category labeling, assistant response tone/completeness review, and function call tagging for backend queries. Verified structured JSON outputs and validated SQL query safety.

Annotated a financial AI advisor dataset including intent classification, transaction and merchant category labeling, assistant response tone/completeness review, and function call tagging for backend queries. Verified structured JSON outputs and validated SQL query safety.

2024 - 2024

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Education

Work History