Data annotation using CVAT tutorial

@InjectAI

I can provide hands-on, personalized CVAT training tailored to your project requirements. We will start from the basics of dataset annotation and gradually cover advanced workflows, object classes, attributes, and exporting annotations in formats suitable for your model. Approach: • Hourly interactive sessions via Zoom/Meet • Screen-sharing to demonstrate CVAT interface and tools • Guided annotation on your project data • Recording of every session for later review • Q&A to clarify concepts and troubleshoot issues in real-time Tech Stack / Tools: • CVAT (latest version, open-source) • Python / OpenCV for optional preprocessing • Annotation formats: COCO, Pascal VOC, YOLO, or custom • Optional integration with machine learning pipelines Deliverables: Recorded session videos for every class Step-by-step notes and annotation best practices Example annotated dataset to use as reference Guidance on project-specific annotation workflow You can see my profile for prior training and annotation projects. I’m ready to start immediately and ensure you gain confidence in CVAT for your project.

@alibanani

Hello, I'm Ali Banani, a professional specializing in software development, web development, social media management, digital marketing, and graphic design. I have over 5 years of experience in Graphic Design and Logo Design. I understand your requirement for learning how to do annotations using CVAT. I will provide clear and professional guidance tailored to your project needs. With my expertise in software development and graphic design, I can help you grasp the basics of CVAT and support your learning journey through hourly classes and recorded sessions. You can view my portfolio at https://www.freelancer.com/u/alibanani Feel free to connect in chat for further discussion. Best regards, Ali Banani

@ajaygupta2

I am a Data Scientist with practical experience in computer vision workflows and dataset preparation. I understand that accurate annotation is critical for building reliable AI models, and I can guide you step by step in using CVAT effectively. I will start with the basics such as task creation, label setup, and annotation types, then gradually move toward project-specific requirements, export formats, and quality control practices. My focus is not only on how to use CVAT, but how to annotate correctly for model performance. Hourly, recorded sessions can be structured according to your project needs, ensuring you gain both practical skills and technical clarity from the beginning.

@vhoc7

Teaching you CVAT for your specific project is exactly what I can help with. As a Computer Vision Engineer with hands-on experience training Object Detection (YOLO, SSD) and Segmentation (UNet++) models, I don't just know how to use CVAT—I know why annotations must be done a specific way to ensure your future AI model actually performs well. Since you want to start with the basics and tailor the learning to your project, here is how we can structure our recorded, hourly sessions: Session 1: The Basics & Setup: Navigating the CVAT interface, mastering keyboard shortcuts for speed, and setting up your first Task/Job with the correct labels. Session 2: Project-Specific Annotation: We will look at your actual dataset. I will guide you on the best practices for your specific use-case (whether it's bounding boxes, polygons, or keypoints) and how to handle edge cases (occlusions, blurry objects) so your future model doesn't get confused. Session 3: Exporting & Next Steps: How to properly dump/export your annotated data into standard formats (YOLO, COCO, Pascal VOC) so it is 100% ready for training.