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I found multiple classes in the dataset that contain vast variety of different people in the same class.
For example, for the person Milos_Twilight with index nm1115471 there are about a 100 photos with different people. Sample two files:
1)
image 10.jpg
rect 470 134 551 214
height width 714 1000
I found multiple classes in the dataset that contain vast variety of different people in the same class.
For example, for the person Milos_Twilight with index nm1115471 there are about a 100 photos with different people. Sample two files:
1)
image 10.jpg
rect 470 134 551 214
height width 714 1000
image 101.jpg
rect 198 161 491 475
height width 1000 678
It seems that there are many classes like that in the dataset.
Does anybody have a complete list of such noisy classes?
Can you provide any recommendations how to fix that problem?
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