What does each column mean in prediction ?

[12343954]

Specifically column 5 （0.9952）, column 6（0.9997），which is the precision？

i know

1. column 0 is index of images
2. column[1-4] is the bbox
3. last column is the index of coco.names

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output：

$ python detect.py --images imgs/dog.jpg --det det

Loading network.....
Network successfully loaded

prediction = tensor([
        [  0.0000,  89.2452, 110.7772, 303.7112, 294.3270,   0.9952,   0.9997, 1.0000],
        [  0.0000, 256.4473,  98.3855, 373.3513, 144.1134,   0.9954,   0.9407, 7.0000],
        [  0.0000,  69.5613, 173.2573, 170.4126, 343.0031,   0.9997,   0.9894, 16.0000]])

dog.jpg              predicted in  0.150 seconds
Objects Detected:    bicycle truck dog
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SUMMARY
----------------------------------------------------------
Task                     : Time Taken (in seconds)

Reading addresses        : 0.000
Loading batch            : 0.178
Detection (1 images)     : 0.150
Output Processing        : 0.000
Drawing Boxes            : 0.004
Average time_per_img     : 0.333
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