a yf@sDddlmZddlmZddlmZddlmZGdddeZdS) )Path)Model)FastSAMPredictor)FastSAMValidatorcs<eZdZdZd fdd Zd fdd Zed d ZZS) FastSAMz FastSAM model interface. Example: ```python from ultralytics import FastSAM model = FastSAM("last.pt") results = model.predict("ultralytics/assets/bus.jpg") ``` FastSAM-x.ptcs:t|dkrd}t|jdvs&Jdtj|dddS)zSCall the __init__ method of the parent class (YOLO) with the updated default model.z FastSAM.ptr>z.ymlz.yamlz/FastSAM models only support pre-trained models.segment)modeltaskN)strrsuffixsuper__init__)selfr  __class__\/var/www/html/django/DPS/env/lib/python3.9/site-packages/ultralytics/models/fastsam/model.pyrs zFastSAM.__init__FNc  s*t||||d}tj||fd|i|S)a Perform segmentation prediction on image or video source. Supports prompted segmentation with bounding boxes, points, labels, and texts. Args: source (str | PIL.Image | numpy.ndarray): Input source. stream (bool): Enable real-time streaming. bboxes (list): Bounding box coordinates for prompted segmentation. points (list): Points for prompted segmentation. labels (list): Labels for prompted segmentation. texts (list): Texts for prompted segmentation. **kwargs (Any): Additional keyword arguments. Returns: (list): Model predictions. )bboxespointslabelstextsprompts)dictrpredict) rsourcestreamrrrrkwargsrrrrrszFastSAM.predictcCsdttdiS)z[Returns a dictionary mapping segment task to corresponding predictor and validator classes.r )Z predictor validator)rr)rrrrtask_map4szFastSAM.task_map)r)FNNNN) __name__ __module__ __qualname____doc__rrpropertyr __classcell__rrrrr s  rN) pathlibrZultralytics.engine.modelrrrvalrrrrrrs