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How to prevent model from mistaking the background as an object? #11861
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@edehino hi, Thank you for reaching out. The issue you're facing with the model mistaking the background as an object can be quite common, especially in complex datasets with multiple object instances. To improve the model's performance and minimize background mistakes, here are a few suggestions:
Lastly, remember that YOLOv5 is maintained by the Ultralytics team, and we constantly rely on contributions, feedback, and support from the community. If you have any further questions or insights, please don't hesitate to engage with the broader community in the discussions section or search through the existing issues. Hope this helps, and best of luck with your project! Ultralytics YOLOv5 team |
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Hi, I know this has been asked before. I have prepared a dataset with two object of interest and trained it using the default parameters. The resulting mAP is good but when I look at the confusion matrix, it shows that 97% of background is predicted as as my object #1.
I tried adding more images with no labels to the training and even the validation set but the result is still the same. Even used yolov5x as a weight but still no improvement.
My dataset is very complex, like in a single photo there are maximum of 200 instances of objects.
Train, test, and val sets are randomly distributed but I failed to come up with a good result.
Anyone who can be of help would be very much appreciated.
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