📦 模型下載https://pub-478929a98a5c440cb22c2241c0bde314.r2.dev/factory_ppe_v20260526/best.pt

👷 Factory PPE 22-attr v20260526

訓練日期 2026-05-27 · 5090-2 GPU 0 batch 128 · MobileNetV3-L · 修 video-mode bug 後第一次「真實」訓練

⚠️ 數字略降但意義不同:這是 PPE 第一次拿到完整 video 訓練資料

v521 / v522 export 用 frames[f] iterate,對 video-mode task meta["frames"] 只有 1 entry → 整支影片只訓第 1 張 frame。v526 改用 cvat_helpers.cvat_frame_iter,video-mode task 整段影片 frame 全進訓。

結果:manifest 從 ~9k 暴衝 184,951 crops (×20)。val_mAP 由 0.977 → 0.960,test_mAP 由 0.957 → 0.946,是因為 test 也從「frame 1 同分布的簡單子集」變成「跨整支影片」更困難更真實的測試集。對 production deploy 是更可靠的數字。

📊 核心指標

0.960
best val mAP @ ep27
0.946
test mAP
0.935
macro F1
184,951
crops 總數

📂 Dataset crops(v522 vs v526 比較)

v522v526×
total crops~9,000184,951×20
train141,392
val27,403
test16,156

per-source(從 cvat #12 task name prefix 判斷)

sourcecrops
other(RAI 自錄場域 / SIEMENS / HONCHUAN / IRODA / FOX 等)102,383
r2ppe25,349
guanxi16,984
sh1713,790
raicvat_p2613,041
raicvat_p1710,087
raicvat_p91,873
cppe51,444

🎯 per-attr test AP(22 attr 完整)

AttrAPF1PRthrvalid samples
hard_hat0.9950.9760.9800.9720.786,575
no_head_protection0.9950.9740.9780.9710.436,330
full_face_mask0.9900.9510.9290.9740.423,536
face_mask0.9920.9560.9440.9690.291,834
no_gloves0.9990.9900.9910.9890.402,953
cotton_gloves0.8060.8210.7550.9010.222,168
rubber_gloves1.0000.9970.9941.0000.132,576
no_protective_clothing1.0000.9970.9980.9960.513,475
cleanroom_suit0.9960.9900.9940.9870.962,062
splash_proof_gown1.0001.0001.0001.0000.992,467
safety_vest0.9630.9340.9290.9380.795,966
safety_shoes0.8750.8400.7730.9200.531,923
no_safety_shoes1.0000.9990.9990.9990.191,822
no_sleeves1.0000.9930.9940.9920.741,958
heartbeat0.8890.8610.8440.8780.943,771
sleeves0.7370.7390.6050.9471.002,017
safety_glasses0.9800.9340.9200.9480.161,670
hair_cover0.7670.8820.8150.9620.001,958
helmet_goggles0.9300.8980.8370.9691.002,275
harness0.9190.8650.8770.8530.7113,064
fall0.9720.9610.9530.9700.792,258
aluminized_apron1.0001.0001.0001.0000.88251

⚠️ 弱點:video-mode 全 frame 進來後曝光的新 gap

→ 下一波重點:補 sleeves / hair_cover / cotton_gloves 的 video 場域標注,或對這些 attr 做 per-attr 增強 (e.g. attr-neg-weight)。

📦 模型下載

factory_ppe_v20260526/best.pt ⬇

⚙️ Hyperparams(完全沿用 v522)

backbone: mobilenetv3_large_100.ra_in1k (4.23M params)
arch:     22-head BCE + partial-label mask
img_size: 384 × 192
batch:    128, epochs: 40 (best ep27, early stopped), patience: 8
lr:       3e-4, wd: 0.01, mixup α: 0.2
aug:      camaug (resize-crop + flip + affine + ±5° rot + ColorJitter + GaussianBlur + RandomErasing)
attr_neg_weight: 全 1.0 (無 per-attr 加權)

# v526 唯一改動:export 改用 cvat_helpers.cvat_frame_iter
#   → video-mode task 整段影片 frame 全進訓(v521/v522 只訓第 1 張)

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