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)
65 lines
1.9 KiB
YAML
65 lines
1.9 KiB
YAML
# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
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# COCO 2017 Keypoints dataset https://cocodataset.org by Microsoft
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# Documentation: https://docs.ultralytics.com/datasets/pose/coco/
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# Example usage: yolo train data=coco-pose.yaml
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# parent
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# ├── ultralytics
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# └── datasets
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# └── coco-pose ← downloads here (20.1 GB)
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# Train/val/test sets as 1) dir: path/to/imgs, 2) file: path/to/imgs.txt, or 3) list: [path/to/imgs1, path/to/imgs2, ..]
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path: coco-pose # dataset root dir
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train: train2017.txt # train images (relative to 'path') 56599 images
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val: val2017.txt # val images (relative to 'path') 2346 images
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test: test-dev2017.txt # 20288 of 40670 images, submit to https://codalab.lisn.upsaclay.fr/competitions/7403
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# Keypoints
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kpt_shape: [17, 3] # number of keypoints, number of dims (2 for x,y or 3 for x,y,visible)
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flip_idx: [0, 2, 1, 4, 3, 6, 5, 8, 7, 10, 9, 12, 11, 14, 13, 16, 15]
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# Classes
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names:
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0: person
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# Keypoint names per class
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kpt_names:
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0:
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- nose
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- left_eye
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- right_eye
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- left_ear
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- right_ear
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- left_shoulder
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- right_shoulder
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- left_elbow
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- right_elbow
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- left_wrist
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- right_wrist
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- left_hip
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- right_hip
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- left_knee
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- right_knee
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- left_ankle
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- right_ankle
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# Download script/URL (optional)
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download: |
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from pathlib import Path
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from ultralytics.utils import ASSETS_URL
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from ultralytics.utils.downloads import download
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# Download labels
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dir = Path(yaml["path"]) # dataset root dir
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urls = [f"{ASSETS_URL}/coco2017labels-pose.zip"]
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download(urls, dir=dir.parent)
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# Download data
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urls = [
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"http://images.cocodataset.org/zips/train2017.zip", # 19G, 118k images
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"http://images.cocodataset.org/zips/val2017.zip", # 1G, 5k images
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"http://images.cocodataset.org/zips/test2017.zip", # 7G, 41k images (optional)
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]
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download(urls, dir=dir / "images", threads=3)
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