A structure for storing masks and their related data in batched format. Implements basic filtering and concatenation.

An attention layer that allows for downscaling the size of the embedding after projection to queries, keys, and values.

Multi-head Attention block with relative position embeddings.

A basic TinyViT layer for one stage. Args: dim (int): Number of input channels. input_resolution (tuple[int]): Input resolution.

Transformer blocks with support of window attention and residual propagation blocks

Image to Patch Embedding.

Positional encoding using random spatial frequencies.

Resizes images to the longest side 'target_length', as well as provides methods for resizing coordinates and boxes. Provides methods for

This model should not be called directly, but is used in ONNX export. It combines the prompt encoder, mask decoder, and mask postprocessing o

r""" TinyViT Block. Args: dim (int): Number of input channels. input_resolution (tuple[int, int]): Input resolution. num_