neural-network - How do I interpret pycaffe classify.py output?

Question

I created a GoogleNet Model via Nvidia DIGITS with two classes (called positive and negative).

If I classify an image with DIGITS, it shows me a nice result like positive: 85.56% and negative: 14.44%.

If it pass that model it into pycaffe's classify.py with the same image, I get a result like array([[ 0.38978559, -0.06033826]], dtype=float32)

So, how do I read/interpret this result? How do I calculate the confidence levels (not sure if this is the right term) shown by DIGITS from the results shown by classify.py?

Answer 1

这个问题使我找到了解决方案。

如日志所示，网络产生三个输出。Classifier#classify只返回第一个输出。因此，例如通过更改predictions = out[self.outputs[0]]为predictions = out[self.outputs[2]]，我得到了所需的值。