初始v3 mixed_10层预测

Question

我为自己的课程重新启动了v3，并尝试在输入图像中本地化检测到的类。

基本上就像这个在图像中寻找行人的例子 http://silverpond.com.au/2016/10/24/pedestrian-detection-using-tensorflow-and-inception.html

所以我能够获得8x8x2048输出

with sess.as_default():
    softmax_tensor = sess.graph.get_tensor_by_name('mixed_10/join:0')
    predictions = sess.run(softmax_tensor, {'DecodeJpeg/contents:0': cv2.imencode('.jpg', img)[1].tostring()})

print len(predictions)

for r in predictions:
    print 'r',len(r)

    for c in r:
        print 'c',len(c)
        print c

这给了我这样的输出：

1
r 8
c 8
[[ 1.47802579  0.45579425  0.32806152 ...,  0.          0.          0.315418  ]
 [ 1.36758661  0.51684511  1.30546498 ...,  0.          0.          0.42971259]
 [ 1.5746814   1.29075444  1.32023144 ...,  0.          0.23419005
   0.11281317]
 ..., 

如何将这些数字转换为我的类的预测？