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I have my custom dataset images of size (1080 x 1920) and I am trying to use yolov3 for object detection. I noticed that yolov3 model accepts an input image size of 416 x 416. So I am in confusion if I should resize the image and apply zero-padding to save the aspect ratio and start my annotation after that OR should I annotate my custom images in original size? And will data argumentation affect the annotation while training? Thanks

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It is best practice to resize the input data to the size a pretrained model expects. A pretrained model has feature detectors for relative differences.

Resizing should be done early in the process so subsequent steps use consistent data. Sometimes resizing is a non-linear process that can use interpolation.

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