Bounding Box Annotation Services
Precise rectangular annotations for object detection. Fast, accurate, and scalable for YOLO, Faster R-CNN, and SSD models with pixel-perfect alignment.
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Foundation for Object Detection Models
Boxes/Month
Pixel Accuracy
Format Ready
Pilot Time
What is Bounding Box Annotation?
Bounding box annotation involves drawing rectangular boxes around objects of interest in images. Each box is labeled with a class name (e.g., "car", "person", "product") and includes precise x, y, width, height coordinates.
This is the foundation for object detection models like YOLO, Faster R-CNN, and SSD. Our annotators ensure tight, consistent boxes with zero overlap errors and pixel-perfect alignment.
Supported Output Formats
YOLO
COCO JSON
Pascal VOC
TFRecord
Custom
Common Use Cases
Object detection in autonomous vehicles
Retail product identification and tracking
Security and surveillance person detection
Wildlife monitoring and animal tracking
Manufacturing defect detection systems
Warehouse inventory management automation
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See what our clients say about working with AI Taggers
"Our fitness app required precise keypoint annotation for 200k human poses. AI Taggers delivered sub-pixel accuracy on all 17 body landmarks, enabling real-time form correction."
Fast Turnaround
Thousands of boxes annotated per day with scalable teams
99%+ Accuracy
Pixel-perfect alignment with zero overlap errors
Quality Assured
3-layer verification process ensures consistency