Ok, so now you have your layer designed! This is how you define it in your .prototxt file:
layer {
name: "LayerName"
type: "Python"
top: "TopBlobName"
bottom: "BottomBlobName"
python_param {
module: "My_Custom_Layer_File"
la...
You can define the layer parameters in the prototxt by using param_str. Once you've done it, here is an example on how you access these paremeters inside the layer class:
def setup(self, bottom, top):
params = eval(self.param_str)
param1 = params["param1"]
param2 = params.g...
In this example we will design a "measure" layer, that outputs the accuracy and a confusion matrix for a binary problem during training and the accuracy, false positive rate and false negative rate during test/validation. Although Caffe already has a Accuracy layer, sometimes you want some...
This example is a custom data layer, that receives a text file with image paths, loads a batch of images and preprocesses them. Just a quick tip, Caffe already has a big range of data layers and probably a custom layer is not the most efficient way if you just want something simple.
My dataLayer.py...
