feat: HSAP platform v2 — modular navigation, quality review, audit log, world model simulation
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)
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CLRNet 使用说明(lane0_copy 数据)
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代码目录:/home/chengfanglu/DATA/BK2/CLRNet-main
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数据目录:/home/chengfanglu/DATA/lane0_copy/(与 UFLD 相同多包布局)
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上游论文原版说明见同目录 README.md。
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一、环境安装
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source ~/miniconda3/etc/profile.d/conda.sh
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cd /home/chengfanglu/DATA/BK2/CLRNet-main
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bash scripts/setup_clrnet_env.sh
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conda activate clrnet_lane
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说明:
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环境名默认 clrnet_lane
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需要 NVIDIA GPU(main.py 使用 .cuda())
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安装包含 PyTorch、mmcv-full、python setup.py develop(编译 NMS)
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二、数据目录
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lane0_copy/
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DATASET/(images、annotations/segmentation_masks、list/)
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DATASET-AddBy-zhangsan-20260615/(增量包)
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lists_merged/(合并列表)
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datasets_registry.json(别名)
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重要:dataset_path 填父目录 lane0_copy,不要只填 DATASET。
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数据集类:clrnet/datasets/mufld.py(MufldLane),从 mask 提取车道折线。
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目录规范:/home/chengfanglu/DATA/lane0_copy/DATASETS_LAYOUT.md
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三、配置文件
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configs/clrnet/clr_resnet18_mufld.py — 推荐,1280x720,多包
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configs/clrnet/clr_resnet18_mufld_smoke.py — 冒烟
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请改 configs/clrnet/clr_resnet18_mufld.py:
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dataset_path = '/home/chengfanglu/DATA/lane0_copy'
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train_packs = ['DATASET']
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(多包:train_packs = ['DATASET', 'DATASET-A'],别名见 datasets_registry.json)
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val_packs = ['DATASET']
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pack_list_name = 'list/train_gt.txt'
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remerge_lists = False
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合并列表输出:lane0_copy/lists_merged/train__DATASET__....txt
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图像与网络参数:
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原图 1280x720
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cut_height 160
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网络输入 800x320
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max_lanes 4
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四、训练
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conda activate clrnet_lane
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cd /home/chengfanglu/DATA/BK2/CLRNet-main
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首次冒烟前先建短列表:
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head -64 /home/chengfanglu/DATA/lane0_copy/DATASET/list/train_gt.txt > /home/chengfanglu/DATA/lane0_copy/DATASET/list/train_gt_smoke.txt
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冒烟:
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python main.py configs/clrnet/clr_resnet18_mufld_smoke.py --gpus 0
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正式:
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python main.py configs/clrnet/clr_resnet18_mufld.py --gpus 0
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权重目录:work_dirs/clr/mufld_r18/(由 config 里 work_dirs 决定)
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多卡示例:--gpus 0 1
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常用修改:
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batch_size = 16
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epochs = 15
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optimizer = dict(type='AdamW', lr=1.0e-3)
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换 train_packs 后请改 total_iter = (144117 // batch_size + 1) * epochs
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五、预生成车道线缓存(推荐)
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首轮会从 mask 现场提线,较慢。可先执行:
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python tools/generate_mufld_lines.py --data-root /home/chengfanglu/DATA/lane0_copy --list DATASET/list/train_gt.txt
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缓存目录:lane0_copy/cache/mufld_lines/
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六、测试与推理
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python main.py configs/clrnet/clr_resnet18_mufld.py --gpus 0 --test --load_from work_dirs/clr/mufld_r18/ckpt/best.pth
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(--load_from 按实际 ckpt 路径填写)
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说明:
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没有 CULane 官方评测
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预测会写成 lines.txt,日志 metric 为占位值
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七、增量数据
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1)建包(与 UFLD 共用脚本):
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python /home/chengfanglu/DATA/lane0_copy/scripts/build_ufld_pack.py --src /path/to/archive --parent /home/chengfanglu/DATA/lane0_copy --engineer zhangsan --date 20260615
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2)config 增加包名:
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train_packs = ['DATASET', 'DATASET-AddBy-zhangsan-20260615']
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remerge_lists = True
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3)重新训练:
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python main.py configs/clrnet/clr_resnet18_mufld.py --gpus 0
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八、路径速查
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代码:/home/chengfanglu/DATA/BK2/CLRNet-main
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数据父目录:/home/chengfanglu/DATA/lane0_copy
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训练配置:configs/clrnet/clr_resnet18_mufld.py
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数据集实现:clrnet/datasets/mufld.py
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安装脚本:scripts/setup_clrnet_env.sh
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