I will data annotation, bounding box, and image labeling in roboflow

Are you building a computer vision model but stuck spending hours manually labeling images?

I'll handle your dataset annotation and labeling so you can focus on training and deploying your model not tagging thousands of images by hand.

What I can do:

• Image classification labeling (organizing images into correct categories/folders)
• Bounding box annotation for object detection (YOLO, Faster R-CNN, SSD formats)
• Polygon/segmentation annotation for instance & semantic segmentation
• Dataset annotation using Roboflow, LabelImg, CVAT, or Makesense.ai
• Dataset cleaning, augmentation, and train/val/test splitting
• Export in any format you need: YOLO (.txt), COCO (JSON), Pascal VOC (XML), CSV

Why work with me:

• Accuracy-focused labeling I double-check classes before delivery
• Fast turnaround even for large datasets
• Clear communication on class definitions and edge cases before starting
• Experience with real ML/CV projects, so I understand what makes a "clean" dataset for training (not just labeling for the sake of it)

Send me your images/videos and class list, and I'll return a ready-to-train dataset