Chengfang Lu
e72bc061c5
Major changes: - New frontend (platform/web/): Vite + React 18 + TypeScript + Tailwind - 4-module navigation: 数据送标 / 模型管理 / 车队管理 / 系统管理 - Data catalog with charts (DMS/ADAS/Lane 3-tab view) - Quality review workflow (标注质检): Good/Fine/Bad scoring with auto-advance - Audit enhancements: batch operations, rejection categories, Feishu notifications - Operation audit log (操作日志) - World model simulation studio (仿真工坊) - Dataset version management with snapshots and diff - ADAS 7-class dataset integration (138K images organized + compressed) - User management with Feishu integration and pagination - CRUD/search/filter on all pages, card layout redesign - PIL-optimized image overlay rendering - Auto-snapshot on build, in_review workflow stage - Removed embedded algorithm code (now in workspace)
39 lines
2.0 KiB
Python
39 lines
2.0 KiB
Python
# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
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from ultralytics.models.yolo.segment import SegmentationValidator
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class FastSAMValidator(SegmentationValidator):
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"""Custom validation class for FastSAM (Segment Anything Model) segmentation in the Ultralytics YOLO framework.
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Extends the SegmentationValidator class, customizing the validation process specifically for FastSAM. 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 (torch.utils.data.DataLoader): The data loader object used for validation.
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save_dir (Path): The directory where validation results will be saved.
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args (SimpleNamespace): Additional arguments for customization of the validation process.
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_callbacks (list): List of callback functions to be invoked during validation.
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metrics (SegmentMetrics): Segmentation metrics calculator for evaluation.
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Methods:
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__init__: Initialize the FastSAMValidator with custom settings for FastSAM.
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"""
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def __init__(self, dataloader=None, save_dir=None, args=None, _callbacks=None):
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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, optional): DataLoader to be used for validation.
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save_dir (Path, optional): Directory to save results.
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args (SimpleNamespace, optional): Configuration for the validator.
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_callbacks (list, optional): List of callback functions to be invoked during validation.
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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, args, _callbacks)
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self.args.task = "segment"
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self.args.plots = False # disable ConfusionMatrix and other plots to avoid errors
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