技術標籤：深度學習演算法Python來自高山深度學習目標檢測SSD演算法pytorch

  如題。
  下面是最終驗證測試集的結果。

Writing bicycle VOC results file
Writing bird VOC results file
Writing boat VOC results file
Writing bottle VOC results file
Writing bus VOC results file
Writing car VOC results file
Writing cat VOC results file
Writing chair VOC results file
 

Writing cow VOC results file
Writing diningtable VOC results file
Writing dog VOC results file
Writing horse VOC results file
Writing motorbike VOC results file
Writing person VOC results file
Writing pottedplant VOC results file
Writing sheep VOC results file
Writing sofa VOC results file
Writing train VOC results file
 

Writing tvmonitor VOC results file
VOC07 metric? Yes
AP for aeroplane = 0.7482
AP for bicycle = 0.8164
AP for bird = 0.6917
AP for boat = 0.6405
AP for bottle = 0.3980
AP for bus = 0.8041
AP for car = 0.8040
AP for cat = 0.8572
AP for chair = 0.5270
AP for cow = 0.7927
AP for diningtable = 0.7147
AP for dog = 0.8265
AP for
 
 horse = 0.8250
AP for motorbike = 0.7983
AP for person = 0.7366
AP for pottedplant = 0.4017
AP for sheep = 0.6665
AP for sofa = 0.7664
AP for train = 0.8302
AP for tvmonitor = 0.7103
Mean AP = 0.7178
~~~~~~~~
Results:
0.748
0.816
0.692
0.641
0.398
0.804
0.804
0.857
0.527
0.793
0.715
0.826
0.825
0.798
0.737
0.402
0.667
0.766
0.830
0.710
0.718
~~~~~~~~

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Results computed with the **unofficial** Python eval code.
Results should be very close to the official MATLAB eval code.
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  待續。