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Input Shape for Training and Inference with Pretrained Models #1112

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@hamac03

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@hamac03

Hi,

I'm currently training models using a backbone like ResNet50, which is pretrained on ImageNet with an input shape of 3x224x224. I was wondering if it's possible to use a larger input size, such as 3x320x320 or 3x416x416, and still benefit from the pretrained weights, or does the input shape need to be strictly 224x224?

Are there any constraints or considerations when using larger input sizes with pretrained models?

Best regards,
Ha

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