Datasets for Computer Vision (2)

explains , , .

(1) Fashion-MNIST(2017):

• has the 70,000 fashion images each connected to a label from 10 classes with 10 classes:
  *Memos:
  
  
  
  
  • 60,000 for train and 10,000 for test.
  
  
  • Each image is 28x28 pixels.
  
  
  
  
  
  



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  (2) in PyTorch.

(2007):

• has the 30,607 object images connected to a label from 257 categories(classes). *Actually, it has 257 categories(classes) against the name Caltech 256.


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  (Large-scale CelebFaces Attributes)(2015):

  
  
  
  
  
  • has the 202,599 celebrity face images each connected to 40 attributes:
    *Memos:
    
    
    
    
    • 162,770 for train, 19,867 for validation and 19,962 for test.
    
    
    • Directly downloading it from from in PyTorch.
    
    
    
    
    
    

    (Canadian Institute For Advanced Research-10)(2009):

    
    
    
    
    
    • has the 60,000 vehicle and animal images each connected to a label from 10 classes:
      *Memos:
      
      
      
      
      • 50,000 for train and 10,000 for test.
      
      
      • Each image is 32x32 pixels.
      
      
      
      
      
      
    
    
    
    • is
      
      
      

      (6) in PyTorch.

    
    
    
    
    
    

    

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