You will get pixel-perfect image and video data annotation using CVAT
Project details
Need high-fidelity datasets to train your machine learning models? I provide precise manual image and video annotation services tailored specifically to computer vision and autonomous system requirements.
What this project includes:
• High-Accuracy Bounding Boxes: Snug fitting with zero background padding bleed.
• Detailed Polygon Masking: Clean, semantic pixel segmentation for complex objects.
• Smooth Video Tracking: Frame-by-frame interpolation to track moving targets perfectly.
• Quality Assurance: Dual-check verification ensuring a 99%+ accuracy rating.
I am highly proficient in CVAT, Labelbox, and Roboflow, and I strictly follow your formatting guidelines (YOLO, COCO, Pascal VOC, or XML). Let's build clean data together!
What this project includes:
• High-Accuracy Bounding Boxes: Snug fitting with zero background padding bleed.
• Detailed Polygon Masking: Clean, semantic pixel segmentation for complex objects.
• Smooth Video Tracking: Frame-by-frame interpolation to track moving targets perfectly.
• Quality Assurance: Dual-check verification ensuring a 99%+ accuracy rating.
I am highly proficient in CVAT, Labelbox, and Roboflow, and I strictly follow your formatting guidelines (YOLO, COCO, Pascal VOC, or XML). Let's build clean data together!
Machine Learning Tools
GPT-3, OpenCV, Python, Python Scikit-Learn, TensorFlowWhat's included
| Service Tiers |
Starter
$30
|
Standard
$60
|
Advanced
$100
|
|---|---|---|---|
| Delivery Time | 2 days | 4 days | 7 days |
Number of Revisions | 2 | 3 | 4 |
Model Validation/Testing | |||
Model Documentation | |||
Data Source Connectivity | - | - | - |
Source Code | - | - | - |
About John Marvin
AI Data Annotator | Computer Vision Specialist
Bulacan, Philippines - 11:23 pm local time
I help machine learning teams eliminate bad data by providing clean, audited datasets.
My technical toolkit includes hands-on experience with:
Tools: CVAT, Labelbox, Roboflow, Scale AI, and V7 Labs.
Image Annotation: Bounding boxes, polygon masks, keypoint labeling, and semantic segmentation.
Video Annotation: Object tracking across frames, interpolation management, and activity tagging.
Text/Data: Named Entity Recognition (NER), text classification, and data cleaning.
Whether you are building an autonomous driving dataset, an e-commerce sorting algorithm, or an object detection model, I ensure strict adherence to your styling guides and edge-case instructions. Let's discuss your project goals!
Steps for completing your project
After purchasing the project, send requirements so John Marvin can start the project.
Delivery time starts when John Marvin receives requirements from you.
John Marvin works on your project following the steps below.
Revisions may occur after the delivery date.
Guideline Review & Sample Alignment
I thoroughly analyze your annotation rulebooks and complete a small 3-image pilot run to verify target classes, boundary padding rules, and cross-check quality expectations with your team.
Precision Bulk Labeling & Quality Review
I execute high-density bounding box or polygon tracking across the full dataset. A comprehensive dual-pass quality audit is conducted on all targets to guarantee a clean 99%+ accuracy rating prior to final delivery.