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neural-networkcaffepycaffenvidia-digits

How do I interpret pycaffe classify.py output?

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?

Solution

  • This issue led me to the solution.

    As the log shows, the network produces three outputs. Classifier#classify only returns the first output. So e.g. by changing predictions = out[self.outputs[0]] to predictions = out[self.outputs[2]], I get the desired values.