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from ultralytics.models.yolo.segment import SegmentationValidator
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from ultralytics.utils.metrics import SegmentMetrics
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class FastSAMValidator(SegmentationValidator):
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"""
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Custom validation class for fast SAM (Segment Anything Model) segmentation in Ultralytics YOLO framework.
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Extends the SegmentationValidator class, customizing the validation process specifically for fast SAM. This class
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sets the task to 'segment' and uses the SegmentMetrics for evaluation. Additionally, plotting features are disabled
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to avoid errors during validation.
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Attributes:
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dataloader: The data loader object used for validation.
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save_dir (str): The directory where validation results will be saved.
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pbar: A progress bar object.
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args: Additional arguments for customization.
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_callbacks: List of callback functions to be invoked during validation.
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"""
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def __init__(self, dataloader=None, save_dir=None, pbar=None, args=None, _callbacks=None):
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"""
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Initialize the FastSAMValidator class, setting the task to 'segment' and metrics to SegmentMetrics.
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Args:
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dataloader (torch.utils.data.DataLoader): Dataloader to be used for validation.
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save_dir (Path, optional): Directory to save results.
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pbar (tqdm.tqdm): Progress bar for displaying progress.
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args (SimpleNamespace): Configuration for the validator.
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_callbacks (dict): Dictionary to store various callback functions.
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Notes:
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Plots for ConfusionMatrix and other related metrics are disabled in this class to avoid errors.
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"""
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super().__init__(dataloader, save_dir, pbar, args, _callbacks)
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self.args.task = "segment"
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self.args.plots = False
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self.metrics = SegmentMetrics(save_dir=self.save_dir, on_plot=self.on_plot)
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