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The Challenges of Labeling in ML Models
Getting the right data and getting good labels is half of the work. The other half is being able to train it and test it properly. And we need to label to a level of precision that has rarely been seen in other use cases. So for example, your dog may be half of the image or maybe 40% of all your pixels. If you want to keep your air bounded, your bounding box on that object needs to be within maybe five pixel or three pixels.