You will get Image Annotation, Polygon, Bounding boxes & data annotation.
Project details
Annotation Tool Selection:
Choose appropriate annotation tools or software based on the nature of the data and annotation tasks. Common tools include Labelbox, VGG Image Annotator (VIA), or custom-built tools.
Annotation Guidelines:
Establish clear and comprehensive annotation guidelines. Define labeling conventions, classes, and any specific criteria for consistent and accurate annotations.
Annotation Process:
Perform the actual annotation according to the established guidelines. This may involve tasks such as drawing bounding boxes, adding labels, or marking specific points of interest.
Quality Control:
Implement a robust quality control process. Double-check annotations to ensure accuracy, consistency, and adherence to guidelines. Correct any errors or inconsistencies.
Client Review:
Provide a sample or partial dataset to the client for review. Incorporate feedback and make necessary adjustments before proceeding with the entire dataset.
Finalize Annotations:
Once the client approves the sample, proceed to annotate the entire dataset. Ensure that the final annotations meet the specified requirements.
Choose appropriate annotation tools or software based on the nature of the data and annotation tasks. Common tools include Labelbox, VGG Image Annotator (VIA), or custom-built tools.
Annotation Guidelines:
Establish clear and comprehensive annotation guidelines. Define labeling conventions, classes, and any specific criteria for consistent and accurate annotations.
Annotation Process:
Perform the actual annotation according to the established guidelines. This may involve tasks such as drawing bounding boxes, adding labels, or marking specific points of interest.
Quality Control:
Implement a robust quality control process. Double-check annotations to ensure accuracy, consistency, and adherence to guidelines. Correct any errors or inconsistencies.
Client Review:
Provide a sample or partial dataset to the client for review. Incorporate feedback and make necessary adjustments before proceeding with the entire dataset.
Finalize Annotations:
Once the client approves the sample, proceed to annotate the entire dataset. Ensure that the final annotations meet the specified requirements.
What's included
| Service Tiers |
Starter
$5
|
Standard
$25
|
Advanced
$150
|
|---|---|---|---|
| Delivery Time | 1 day | 2 days | 3 days |
Number of Revisions | 1 | 1 | 2 |
Number of Scenarios | 1 | 1 | 1 |
Model Validation/Testing | - | - | - |
Model Documentation | - | - | - |
Data Source Connectivity | - | - | - |
Source Code | - | - | - |
About Azhar
Annotation & QA Specialist | Ensuring Accuracy and Consistency
Islamabad, Pakistan - 1:10 am local time
Projects:
Golden Algo Project (Client: Audi)
Lamborghini Self-Driven Cars Validation
Spoors Birds Annotation Project
CARIAD Traffic Sign Recognition
Autonomous Cars Object Detection
Video Annotation of Rugby Game
DML (Digital Matrix LED)
My Expertise Includes:
Data Annotation: Skilled in using CVAT, Roboflow, Labelme, Labelbox, and proprietary tools for annotating various modules like 3D/2D bounding boxes, lane detection, traffic sign detection, module light assistance, and scene recognition.
Video Annotation: Proficient in VGG for video annotation, handling temporal segmentation and timestamps.
Quality Assurance: Ensuring high-quality outcomes through meticulous attention to detail and rigorous quality assurance processes.
One aspect that sets me apart is my commitment to understanding each client’s specific needs and vision. By maintaining open communication throughout the project, I ensure the final deliverable aligns perfectly with your expectations.
Leadership Experience: Currently, I lead a team of 20 professional annotators skilled in various annotation types. This role involves managing resources, overseeing quality assurance, and ensuring timely, accurate project completion to meet client expectations. I also provide guidance to team members, fostering collaboration and skill enhancement to maintain high standards across all projects.
Experience:
Senior Data Annotator at Maanz AI (2020 - 2024)
Led a team of annotators to deliver high-quality annotations for various modules, including 3D/2D bounding boxes, lane detection, and scene recognition.
Managed quality assurance processes to ensure accuracy and consistency in annotations.
Collaborated with high-profile clients such as Audi and Lamborghini on autonomous vehicle projects.
Output Data Formats:
COCO, YOLO
XML, TXT
CSV, JSON
Excel, Word, XLSX
Or any other required format
I'm confident that my leadership experience, attention to detail, and dedication to quality assurance will bring efficiency and value to your project. Please feel free to reach out to discuss how my skills and experience can further benefit your team.
Steps for completing your project
After purchasing the project, send requirements so Azhar can start the project.
Delivery time starts when Azhar receives requirements from you.
Azhar works on your project following the steps below.
Revisions may occur after the delivery date.
Perform the actual annotation according to the established guidelines.