Accurate prediction box custom vision

Student xyz 21 Reputation points
2021-09-10T14:16:23.743+00:00

I would like to know how to make the red prediction boxes more accurate.

I am extremely accurate in providing the exact region with the according label but I don't see the accuracy of the red box getting better.
Examples:

region marking plus labeling:
131130-image.png

Quick test result
131136-image.png

Desired test result accuracy
131263-image.png

Hope to get some input from the community

Azure Computer Vision
Azure Computer Vision
An Azure artificial intelligence service that analyzes content in images and video.
381 questions
Azure AI Custom Vision
Azure AI Custom Vision
An Azure artificial intelligence service and end-to-end platform for applying computer vision to specific domains.
250 questions
Azure AI services
Azure AI services
A group of Azure services, SDKs, and APIs designed to make apps more intelligent, engaging, and discoverable.
2,921 questions
{count} votes

2 answers

Sort by: Most helpful
  1. GiftA-MSFT 11,171 Reputation points
    2021-09-13T15:47:34.857+00:00

    Hi, thanks for clarifying. The following document describes how to improve custom vision model. Based on the information you provided above, my recommendation would be to:

    • Be aware of input image requirements
    • Provide at least 30 images per tag
    • Add more images and balance data; retrain
    • Add images with varying background, lighting, object size, camera angle, and style; retrain
    • Use new image(s) to test prediction
    • Modify existing training data according to prediction results (you can use prediction images for further training)

    Hope this helps!

    0 comments No comments

  2. Student xyz 21 Reputation points
    2021-09-13T16:16:59.363+00:00

    Thanks for answering. I already have tried most of the points you mentioned but I also see some things I haven't tried. I appreciate your help!

    0 comments No comments

Your answer

Answers can be marked as Accepted Answers by the question author, which helps users to know the answer solved the author's problem.