How to get probabilties in caffe model

Question

I am using Squeezenet,the final few layers look like this,Im not really sure what exactly to change for me to be able to avail probabilities,

layer {
  name: "loss"
  type: "SoftmaxWithLoss"
  bottom: "pool10"
  bottom: "label"
  top: "loss"
  #include {
  #  phase: TRAIN
  #}
}
layer {
  name: "accuracy"
  type: "Accuracy"
  bottom: "pool10"
  bottom: "label"
  top: "accuracy"
  #include {
  #  phase: TEST
  #}
}
layer {
  name: "accuracy_top5"
  type: "Accuracy"
  bottom: "pool10"
  bottom: "label"
  top: "accuracy_top5"
  #include {
  #  phase: TEST
  #}
  accuracy_param {
    top_k: 5
  }
} 

How do i get probabilities instead of binary outputs? Thanks in advance.

Answer 1

In python you can do something of this form :

    caffe.set_mode_gpu()    
    net = caffe.Net('path/to/deploy.prototxt', 'path/to/mode.caffemodel',caffe.TEST)

    for image in images:

        im = np.array(caffe.io.load_image(image))
        im = np.array(im,dtype=np.float32)
        im = im.transpose(2,0,1)
        net.blobs['data'].reshape(1,*im.shape)
        net.blobs['data'].data[...] = im
        net.forward()
        print(net.blobs['prob'].data)

For a more in depth understanding of the code snippet and other useful features of caffe network surgery, I recommend this link .

Answer 2

What you are missing is a "Softmax" layer that "converts" your predictions into per-class probabilities

layer {
  name: "prob"
  type: "Softmax"
  bottom: "pool10"
  top: "prob"
}

Note that your loss layer, "SoftmaxWithLoss" does this very same probability calculation internally (in theory you may get these probabilities as a second top of the loss layer, but for some.e reason I never managed to make it work. PR #5828 suppose to make it work)