FPh jddlmZddlZddlmZddlmZddlmZmZGddejZ y) )ListN)nn) MaskDecoder)ImageEncoderViT PromptEncoderc leZdZUdZdZeed<dZeed< dde de de d e ed e ed d f fd Z xZS)Samah Sam (Segment Anything Model) is designed for object segmentation tasks. It uses image encoders to generate image embeddings, and prompt encoders to encode various types of input prompts. These embeddings are then used by the mask decoder to predict object masks. Attributes: mask_threshold (float): Threshold value for mask prediction. image_format (str): Format of the input image, default is 'RGB'. image_encoder (ImageEncoderViT): The backbone used to encode the image into embeddings. prompt_encoder (PromptEncoder): Encodes various types of input prompts. mask_decoder (MaskDecoder): Predicts object masks from the image and prompt embeddings. pixel_mean (List[float]): Mean pixel values for image normalization. pixel_std (List[float]): Standard deviation values for image normalization. gmask_thresholdRGB image_format image_encoderprompt_encoder mask_decoder pixel_mean pixel_stdreturnNc(t|||_||_||_|j dt j|jdddd|j dt j|jddddy)a Initialize the Sam class to predict object masks from an image and input prompts. Note: All forward() operations moved to SAMPredictor. Args: image_encoder (ImageEncoderViT): The backbone used to encode the image into image embeddings. prompt_encoder (PromptEncoder): Encodes various types of input prompts. mask_decoder (MaskDecoder): Predicts masks from the image embeddings and encoded prompts. pixel_mean (List[float], optional): Mean values for normalizing pixels in the input image. Defaults to (123.675, 116.28, 103.53). pixel_std (List[float], optional): Std values for normalizing pixels in the input image. Defaults to (58.395, 57.12, 57.375). rrFrN) super__init__rrrregister_buffertorchTensorview)selfrrrrr __class__s mC:\Users\daisl\Desktop\realtime-object-detection\venv\Lib\site-packages\ultralytics/models/sam/modules/sam.pyrz Sam.__init__$s. *,( \5<< +C+H+HQPQ+RTYZ [%,,y*A*F*Fr1a*PRWX))g33333^@gR]@gRY@)g(\2M@g(\L@gL@)__name__ __module__ __qualname____doc__r float__annotations__r strrrrrr __classcell__)rs@rr r sz  NEL##r-s( !4.Y")).Yr