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)
This commit is contained in:
@@ -1,207 +1,8 @@
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======================================================================
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【ddaw_1124】YOLO 检测 path: /home/chengfanglu/DATA/DMS/DATASET/gyp/ddaw_1124
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======================================================================
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当前划分: train=3824 val=424 test=0 合计=4248
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类别数(nc): 9 类别ID: [0, 1, 2, 3, 4, 5, 6, 7, 8]
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--- 当前：含该类别的图片数（按 split）---
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cls train val val% test 合计
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0 3072 348 10.2% 0 3420
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1 686 65 8.7% 0 751
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2 1827 210 10.3% 0 2037
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3 619 71 10.3% 0 690
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4 279 29 9.4% 0 308
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5 881 99 10.1% 0 980
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6 2415 273 10.2% 0 2688
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7 659 64 8.9% 0 723
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8 138 15 9.8% 0 153
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当前 val 占比: min=8.7% max=10.3% 极差=1.7% (目标≈10%)
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✓ 当前各类 val 比例已较均衡
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--- 分层重分后(模拟, val_ratio=0.1, seed=42) ---
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train=3823 val=425
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cls train val val%
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0 3074 346 10.1%
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1 674 77 10.3%
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2 1834 203 10.0%
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3 620 70 10.1%
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4 277 31 10.1%
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5 882 98 10.0%
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6 2423 265 9.9%
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7 651 72 10.0%
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8 138 15 9.8%
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重分后 val 占比: min=9.8% max=10.3% 极差=0.4%
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✓ 分层后各类 val 比例均衡（极差≤2%）
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======================================================================
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【addw_0523】YOLO 检测 path: /home/chengfanglu/DATA/DMS/DATASET/gyp/addw_0523
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======================================================================
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当前划分: train=2375 val=594 test=0 合计=2969
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类别数(nc): 4 类别ID: [0, 1, 2, 3]
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--- 当前：含该类别的图片数（按 split）---
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cls train val val% test 合计
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0 1367 370 21.3% 0 1737
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1 415 120 22.4% 0 535
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2 1018 229 18.4% 0 1247
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3 1812 445 19.7% 0 2257
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当前 val 占比: min=18.4% max=22.4% 极差=4.1% (目标≈10%)
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⚠ 当前各类 val 比例不均衡
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--- 分层重分后(模拟, val_ratio=0.1, seed=42) ---
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train=2671 val=298
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cls train val val%
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0 1565 172 9.9%
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1 481 54 10.1%
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2 1121 126 10.1%
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3 2029 228 10.1%
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重分后 val 占比: min=9.9% max=10.1% 极差=0.2%
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✓ 分层后各类 val 比例均衡（极差≤2%）
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======================================================================
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【isa_detect】YOLO 检测 path: /home/chengfanglu/DATA/DMS/DATASET/gyp/isa_detect
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======================================================================
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当前划分: train=50480 val=9584 test=0 合计=60064
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类别数(nc): 4 类别ID: [0, 1, 2, 3]
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--- 当前：含该类别的图片数（按 split）---
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cls train val val% test 合计
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0 15871 2971 15.8% 0 18842
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1 33355 7060 17.5% 0 40415
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2 7348 1204 14.1% 0 8552
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3 14715 2429 14.2% 0 17144
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当前 val 占比: min=14.1% max=17.5% 极差=3.4% (目标≈10%)
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⚠ 当前各类 val 比例不均衡
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--- 分层重分后(模拟, val_ratio=0.1, seed=42) ---
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train=54066 val=5940
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cls train val val%
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0 16883 1902 10.1%
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1 36344 4013 9.9%
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2 7693 855 10.0%
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3 15435 1707 10.0%
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重分后 val 占比: min=9.9% max=10.1% 极差=0.2%
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✓ 分层后各类 val 比例均衡（极差≤2%）
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======================================================================
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【dam_0516】YOLO 检测 path: /home/chengfanglu/DATA/DMS/DATASET/gyp/dam_0516
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======================================================================
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当前划分: train=3780 val=1890 test=0 合计=5670
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类别数(nc): 15 类别ID: [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14]
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--- 当前：含该类别的图片数（按 split）---
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cls train val val% test 合计
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0 2582 1337 34.1% 0 3919
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1 726 373 33.9% 0 1099
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2 1670 829 33.2% 0 2499
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3 784 395 33.5% 0 1179
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4 266 136 33.8% 0 402
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5 1141 542 32.2% 0 1683
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6 2066 1050 33.7% 0 3116
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7 670 324 32.6% 0 994
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8 445 217 32.8% 0 662
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9 1088 528 32.7% 0 1616
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10 306 164 34.9% 0 470
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11 838 464 35.6% 0 1302
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12 883 489 35.6% 0 1372
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13 3700 1843 33.2% 0 5543
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14 360 151 29.5% 0 511
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当前 val 占比: min=29.5% max=35.6% 极差=6.1% (目标≈10%)
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⚠ 当前各类 val 比例不均衡
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--- 分层重分后(模拟, val_ratio=0.1, seed=42) ---
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train=5104 val=566
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cls train val val%
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0 3525 394 10.1%
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1 986 113 10.3%
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2 2240 259 10.4%
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3 1074 105 8.9%
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4 362 40 10.0%
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5 1497 186 11.1%
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6 2826 290 9.3%
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7 896 98 9.9%
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8 595 67 10.1%
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9 1473 143 8.8%
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10 423 47 10.0%
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11 1180 122 9.4%
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12 1241 131 9.5%
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13 4988 555 10.0%
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14 459 52 10.2%
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重分后 val 占比: min=8.8% max=11.1% 极差=2.2%
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~ 分层后明显改善，少数类因样本极少会有小幅偏差
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======================================================================
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【yoloface-0726】YOLO 检测 path: /home/chengfanglu/DATA/DMS/DATASET/gyp/yoloface-0726
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======================================================================
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当前划分: train=4145 val=1464 test=0 合计=5609
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类别数(nc): 1 类别ID: [0]
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--- 当前：含该类别的图片数（按 split）---
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cls train val val% test 合计
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0 4137 1462 26.1% 0 5599
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当前 val 占比: min=26.1% max=26.1% 极差=0.0% (目标≈10%)
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✓ 当前各类 val 比例已较均衡
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--- 分层重分后(模拟, val_ratio=0.1, seed=42) ---
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train=4970 val=551
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cls train val val%
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0 4960 551 10.0%
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重分后 val 占比: min=10.0% max=10.0% 极差=0.0%
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✓ 分层后各类 val 比例均衡（极差≤2%）
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======================================================================
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【isa_class_0116】分类(文件夹) path: /home/chengfanglu/DATA/DMS/DATASET/gyp/isa_class_0116
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======================================================================
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split: ['test', 'train'] 类别数: 92 总图片: 61747
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--- 每类图片数（前20类 + 汇总）---
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class test train
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005 43 393
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010 55 501
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015 47 424
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020 67 604
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030 214 1933
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040 152 1369
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050 279 2513
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060 224 2024
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070 179 1614
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080 285 2572
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090 116 1045
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100 207 1866
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110 88 794
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120 156 1407
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130 47 429
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arrow_right 126 1138
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arrow_up 38 350
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bycycle 40 368
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dis_005 30 279
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dis_010 23 213
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(仅列前20类，共92类)
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当前为 train/test 结构（无 val）；若需 val 请用 stratified_split.py classify --src-split train
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若从 train 按类划 10% val: val% min=8.3% max=11.8% 极差=3.4%
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test: 92类 min=1 max=310 avg=67 合计=6133
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train: 92类 min=17 max=2792 avg=604 合计=55614
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======================================================================
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【dam_src_0417】原始 jpg+xml path: /home/chengfanglu/DATA/DMS/DATASET/gyp/dam_src_0417
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======================================================================
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src_data_0417_pick: jpg=2455 xml=2455 (无 YOLO 标签，待转换后按类划分)
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[adas]
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Pedestrain: 19730
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Car: 241764
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Truck: 87538
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Bus: 6804
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Motor-vehicles: 38378
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Tricycle: 5654
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cones: 6419
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