Anil Adhav

Key Skills

Software

Appen

Clickworker

CVAT

Dataturk

Labelbox

Label Studio

Remotasks

Scale AI

Other

Top Subject Matter

No subject matter listed

Top Data Types

3D Sensor

Image

Video

Top Task Types

Audio Recording

Bounding Box

Polygon

Prompt Response Writing SFT

Segmentation

Freelancer Overview

I have strong hands-on experience in data labeling and AI training data preparation, specializing in both image and video annotation. I worked with DataForce on high-quality AI projects, including annotation tasks for NVIDIA, where I labeled defects such as dents, scratches, cracks, displacement, Vehicles, aeroplan, pedestrian using polygon, bounding box, and CVAT, Label Studio, and segmentation tools like Data Force Sage Maker Annotation Editor, Data Force Annotation Edito . My work involved following strict guidelines, handling large datasets, and consistently meeting throughput and quality requirements. What sets me apart is my ability to deliver high-accuracy annotations with consistency and speed. I have experience in QC processes, collaborating with QA teams, and resolving annotation ambiguities. My technical understanding of annotation tools, strong attention to detail, and commitment to quality ensure that the AI training data I produce is reliable and ready for advanced computer vision model development.

Labeling Experience

Sparrow 3.0 PlaneTurn

OtherVideoPolygon

Worked on high-precision video annotation for airport runway operations using DataForce Annotation Editor. Labeled airplanes and 60+ airport objects (wings, engines, trucks, buses, loaders, GPU units, cargo equipment, etc.) using polygon segmentation and keyframe interpolation. Applied occlusion factors (0%, 30%, 60%, 90%) and ensured accurate object tracking across video frames. Scope & Tasks: Segmented objects frame-by-frame using polygons. Tracked objects through full video sequences with interpolation. Annotated all aircraft parts and ground service vehicles. Applied strict visibility and occlusion rules for each annotation. Ensured separate labeling for each object instance. Quality Measures: Tight, accurate polygons for planes and critical equipment. Consistent tracking across frames with clean keyframes. Avoided over-labeling and unnecessary polygon points. Followed all DataForce labeling guidelines for precision and consistency.

Worked on high-precision video annotation for airport runway operations using DataForce Annotation Editor. Labeled airplanes and 60+ airport objects (wings, engines, trucks, buses, loaders, GPU units, cargo equipment, etc.) using polygon segmentation and keyframe interpolation. Applied occlusion factors (0%, 30%, 60%, 90%) and ensured accurate object tracking across video frames. Scope & Tasks: Segmented objects frame-by-frame using polygons. Tracked objects through full video sequences with interpolation. Annotated all aircraft parts and ground service vehicles. Applied strict visibility and occlusion rules for each annotation. Ensured separate labeling for each object instance. Quality Measures: Tight, accurate polygons for planes and critical equipment. Consistent tracking across frames with clean keyframes. Avoided over-labeling and unnecessary polygon points. Followed all DataForce labeling guidelines for precision and consistency.

2025 - 2025

Car Damage image labeling

Label StudioImageBounding BoxPolygon

Project Summary Worked on annotating car damages—dents, scratches, cracks, and displacements—using the DataForce SageMaker Annotation Editor, and Label Studio. The task involved drawing precise polygons/brush masks around visible damaged areas while following strict labeling rules. Scope Annotated four damage types using polygon and brush tools. Labeled only visible areas without crossing image boundaries. Excluded glass panels, wheels, and external objects. Tasks Performed Created accurate polygon annotations. Grouped dense small scratches. Applied correct class colors: Scratch (Green), Dent (Orange), Crack (Blue), Displacement (Red). Project Size 1500 images, throughput 50/hr, duration 14–21 June, tool: SageMaker Editor. Quality Measures Followed strict guidelines; rework had to be corrected immediately. Ensured consistent, clean, and boundary-accurate annotations.

Project Summary Worked on annotating car damages—dents, scratches, cracks, and displacements—using the DataForce SageMaker Annotation Editor, and Label Studio. The task involved drawing precise polygons/brush masks around visible damaged areas while following strict labeling rules. Scope Annotated four damage types using polygon and brush tools. Labeled only visible areas without crossing image boundaries. Excluded glass panels, wheels, and external objects. Tasks Performed Created accurate polygon annotations. Grouped dense small scratches. Applied correct class colors: Scratch (Green), Dent (Orange), Crack (Blue), Displacement (Red). Project Size 1500 images, throughput 50/hr, duration 14–21 June, tool: SageMaker Editor. Quality Measures Followed strict guidelines; rework had to be corrected immediately. Ensured consistent, clean, and boundary-accurate annotations.

2024 - 2024

Sparrow 2.0 PlaneTurn

CVATVideoBounding BoxPolygon

Worked on high-precision video annotation for airport runway operations using DataForce Annotation Editor, and CVAT. Labeled airplanes and 60+ airport objects (wings, engines, trucks, buses, loaders, GPU units, cargo equipment, etc.) using polygon segmentation and keyframe interpolation. Applied occlusion factors (0%, 30%, 60%, 90%) and ensured accurate object tracking across video frames. Scope & Tasks: Segmented objects frame-by-frame using polygons. Tracked objects through full video sequences with interpolation. Annotated all aircraft parts and ground service vehicles. Applied strict visibility and occlusion rules for each annotation. Ensured separate labeling for each object instance. Quality Measures: Tight, accurate polygons for planes and critical equipment. Consistent tracking across frames with clean keyframes. Avoided over-labeling and unnecessary polygon points. Followed all DataForce labeling guidelines for precision and consistency.

Worked on high-precision video annotation for airport runway operations using DataForce Annotation Editor, and CVAT. Labeled airplanes and 60+ airport objects (wings, engines, trucks, buses, loaders, GPU units, cargo equipment, etc.) using polygon segmentation and keyframe interpolation. Applied occlusion factors (0%, 30%, 60%, 90%) and ensured accurate object tracking across video frames. Scope & Tasks: Segmented objects frame-by-frame using polygons. Tracked objects through full video sequences with interpolation. Annotated all aircraft parts and ground service vehicles. Applied strict visibility and occlusion rules for each annotation. Ensured separate labeling for each object instance. Quality Measures: Tight, accurate polygons for planes and critical equipment. Consistent tracking across frames with clean keyframes. Avoided over-labeling and unnecessary polygon points. Followed all DataForce labeling guidelines for precision and consistency.

2024 - 2024

Sparrow PlaneTurn

OtherVideoPolygon

Worked on high-precision video annotation for airport runway operations using DataForce Annotation Editor. Labeled airplanes and 60+ airport objects (wings, engines, trucks, buses, loaders, GPU units, cargo equipment, etc.) using polygon segmentation and keyframe interpolation. Applied occlusion factors (0%, 30%, 60%, 90%) and ensured accurate object tracking across video frames. Scope & Tasks: Segmented objects frame-by-frame using polygons. Tracked objects through full video sequences with interpolation. Annotated all aircraft parts and ground service vehicles. Applied strict visibility and occlusion rules for each annotation. Ensured separate labeling for each object instance. Quality Measures: Tight, accurate polygons for planes and critical equipment. Consistent tracking across frames with clean keyframes. Avoided over-labeling and unnecessary polygon points. Followed all DataForce labeling guidelines for precision and consistency.

Worked on high-precision video annotation for airport runway operations using DataForce Annotation Editor. Labeled airplanes and 60+ airport objects (wings, engines, trucks, buses, loaders, GPU units, cargo equipment, etc.) using polygon segmentation and keyframe interpolation. Applied occlusion factors (0%, 30%, 60%, 90%) and ensured accurate object tracking across video frames. Scope & Tasks: Segmented objects frame-by-frame using polygons. Tracked objects through full video sequences with interpolation. Annotated all aircraft parts and ground service vehicles. Applied strict visibility and occlusion rules for each annotation. Ensured separate labeling for each object instance. Quality Measures: Tight, accurate polygons for planes and critical equipment. Consistent tracking across frames with clean keyframes. Avoided over-labeling and unnecessary polygon points. Followed all DataForce labeling guidelines for precision and consistency.

2023 - 2024

Education

Work History