I'm wondering how dynamic input size is supported in Nanodet.
I noticed that there's no padding in the input image as long as width and height are divisible to 32. I train the model with shape 192x192, but during inference I can use it with various input sizes.
Adaptive pooling layers are typically used to support dynamic input size, but I didn't see them in the backbone.
How is it handled in Nanodet?
Hello,
I'm wondering how dynamic input size is supported in Nanodet.
I noticed that there's no padding in the input image as long as width and height are divisible to 32. I train the model with shape 192x192, but during inference I can use it with various input sizes.
Adaptive pooling layers are typically used to support dynamic input size, but I didn't see them in the backbone. How is it handled in Nanodet?