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)
24 lines
879 B
Python
24 lines
879 B
Python
# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
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def adjust_bboxes_to_image_border(boxes, image_shape, threshold=20):
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"""Adjust bounding boxes to stick to image border if they are within a certain threshold.
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Args:
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boxes (torch.Tensor): Bounding boxes with shape (N, 4) in xyxy format.
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image_shape (tuple): Image dimensions as (height, width).
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threshold (int): Pixel threshold for considering a box close to the border.
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Returns:
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(torch.Tensor): Adjusted bounding boxes with shape (N, 4).
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"""
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# Image dimensions
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h, w = image_shape
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# Adjust boxes that are close to image borders
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boxes[boxes[:, 0] < threshold, 0] = 0 # x1
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boxes[boxes[:, 1] < threshold, 1] = 0 # y1
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boxes[boxes[:, 2] > w - threshold, 2] = w # x2
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boxes[boxes[:, 3] > h - threshold, 3] = h # y2
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return boxes
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