Pleae, can you tell me how should I preprosess data while using transfer learning? I mean obligatory preprosessing.
For example, if I want to use resnet50, can I have training images with size 100*100*3? or 512*512*3? Or I should convert them to 224*224*3?
Also, should I normalize data to mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]?
Should I also use /255?
Maybe smth else?
I would be very grateful if you provide explanations and links to articles
For example, if I want to use resnet50, can I have training images with size 100*100*3? or 512*512*3? Or I should convert them to 224*224*3?
Also, should I normalize data to mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]?
Should I also use /255?
Maybe smth else?
I would be very grateful if you provide explanations and links to articles