I have a question regarding the EfficientNetV2 family of models. If my understanding is correct there are 6 models under this family - B0 to B1 & S are the comparatively smaller models while M & L are the larger ones. However, I'm having difficulty understanding the expected input dimensions (image resolution) for these models.
In my dataset, the image size is 400x400. I can convolve the images to reduce the size or add zero padding to increase it, but I'm unsure about the model's actual expectations.
I have been referring to the paper EfficientNetV2: Smaller Models and Faster Training for guidance, but I might be missing something. I would greatly appreciate it if anyone could provide some insights or direct me to the correct information.
Thank you in advance for your help! Cheers!
(Edit: While looking further into the problem, I think we can simply provide the target_size in the
tf.keras.preprocessing.image.ImageDataGenerator function & it will resize the input image to the given resolution? However, I'd still like to get an answer to my original question, if possible)