VOC 07
检测结果
compute mAP
{'bus': 229, 'person': 4690, 'boat': 290, 'dog': 510, 'horse': 362, 'aeroplane': 306, 'chair': 798, 'bottle': 505, 'cat': 376, 'diningtable': 215, 'motorbike': 339, 'bird': 486, 'pottedplant': 514, 'bicycle': 353, 'sheep': 257, 'cow': 259, 'tvmonitor': 324, 'car': 1250, 'train': 297, 'sofa': 248}
78.50% = aeroplane AP
69.27% = bicycle AP
73.40% = bird AP
74.93% = boat AP
62.74% = bottle AP
83.17% = bus AP
73.59% = car AP
86.30% = cat AP
72.41% = chair AP
77.80% = cow AP
72.07% = diningtable AP
84.35% = dog AP
75.40% = horse AP
74.01% = motorbike AP
70.48% = person AP
70.45% = pottedplant AP
68.00% = sheep AP
75.76% = sofa AP
84.15% = train AP
78.23% = tvmonitor AP
mAP = 75.25%
训练日志
$ python train.py
Epoch 0/49
----------
train Loss: 9.3544
save model
Epoch 1/49
----------
train Loss: 7.4459
save model
Epoch 2/49
----------
train Loss: 7.1511
save model
Epoch 3/49
----------
train Loss: 6.9450
save model
Epoch 4/49
----------
train Loss: 6.7656
save model
Epoch 5/49
----------
train Loss: 6.6077
save model
Epoch 6/49
----------
train Loss: 6.4264
save model
Epoch 7/49
----------
train Loss: 6.2750
save model
Epoch 8/49
----------
train Loss: 6.0318
save model
Epoch 9/49
----------
train Loss: 5.7777
save model
Epoch 10/49
----------
train Loss: 5.4760
save model
Epoch 11/49
----------
train Loss: 5.1784
save model
Epoch 12/49
----------
train Loss: 4.8067
save model
Epoch 13/49
----------
train Loss: 4.4603
save model
Epoch 14/49
----------
train Loss: 4.1291
save model
Epoch 15/49
----------
train Loss: 3.7810
save model
Epoch 16/49
----------
train Loss: 3.4259
save model
Epoch 17/49
----------
train Loss: 3.1166
save model
Epoch 18/49
----------
train Loss: 2.8041
save model
Epoch 19/49
----------
train Loss: 2.4853
save model
Epoch 20/49
----------
train Loss: 2.2107
save model
Epoch 21/49
----------
train Loss: 1.9424
save model
Epoch 22/49
----------
train Loss: 1.7307
save model
Epoch 23/49
----------
train Loss: 1.5518
save model
Epoch 24/49
----------
train Loss: 1.3712
save model
Epoch 25/49
----------
train Loss: 1.2174
save model
Epoch 26/49
----------
train Loss: 1.1142
save model
Epoch 27/49
----------
train Loss: 1.0305
save model
Epoch 28/49
----------
train Loss: 0.9270
save model
Epoch 29/49
----------
train Loss: 0.8465
save model
Epoch 30/49
----------
train Loss: 0.7739
save model
Epoch 31/49
----------
train Loss: 0.7228
save model
Epoch 32/49
----------
train Loss: 0.6765
save model
Epoch 33/49
----------
train Loss: 0.6264
save model
Epoch 34/49
----------
train Loss: 0.5932
save model
Epoch 35/49
----------
train Loss: 0.5646
save model
Epoch 36/49
----------
train Loss: 0.5359
save model
Epoch 37/49
----------
train Loss: 0.4941
save model
Epoch 38/49
----------
train Loss: 0.4682
save model
Epoch 39/49
----------
train Loss: 0.4482
save model
Epoch 40/49
----------
train Loss: 0.4276
save model
Epoch 41/49
----------
train Loss: 0.4048
save model
Epoch 42/49
----------
train Loss: 0.3874
save model
Epoch 43/49
----------
train Loss: 0.3759
save model
Epoch 44/49
----------
train Loss: 0.3607
save model
Epoch 45/49
----------
train Loss: 0.3415
save model
Epoch 46/49
----------
train Loss: 0.3327
save model
Epoch 47/49
----------
train Loss: 0.3222
save model
Epoch 48/49
----------
train Loss: 0.3141
save model
Epoch 49/49
----------
train Loss: 0.2978
save model
Training complete in 214m 30s