Annotation or labeling is a fundamental part of what makes many machine learning projects function accurately. Annotating your data takes work. At Nanonets we have a world class team of annotators which can help you to annotate your data (paid plans only).
If you are uploading data for object detection following are some guideline you should follow to make your model more accurate.

  • Tight Bounding Boxes

"The boxes should be as small as possible to fit the entire object"

  • Completeness

"Make sure you have annotated all objects from all categories in an image. Missing any objects hampers the model’s learning"

  •  Consistency across images

"You should maintain uniformity in annotations across all images in case your object has a certain degree of subjectivity in identifying them. For instance, how damaged the concrete surface should be to call it a “crack” must be the same for all images"

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