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FocalLossLayer is midified from SoftmaxWithLossLayer. More info please refer to paper: Focal Loss for Dense Object Detection. If it helps your research, Please consider give me a Star.

1. Clone this repository

   git clone https://github.com/liaomingg/focal_loss_layer.git

2. Modify your caffe.proto

   // Add the next contents to message LayerParameter
   message LayerParameter {
       optional FocalLossParameter focal_loss_param = 151; // select a id.
   }
   
   // Add the next contents to your caffe.proto
   // Message that stores parameter used by FocalLossLayer
   message FocalLossParameter {
       // loss = -alpha * (1 - pk)^gamma * ln(pk)
       // alpha is a parameter which scale the loss
       optional float alpha = 1 [default = 0.25];
       optional float gamma = 2 [default = 2.00];
   }
   

3. Add source file to your Caffe

   Add focal_loss_layer.hpp to Caffe/include/caffe/layers/
   Add focal_loss_layer.cpp to Caffe/src/caffe/layers/
   Add focal_loss_layer.cu to Caffe/src/caffe/layers/
   

4. Compile your Caffe

1. Write codes such as follows in your prototxt file.

   layer {
       name: "focal_loss"
       type: "FocalLoss"
       bottom: "conv_cls"
       bottom: "label"
       top: "loss"
       include {
           phase: TRAIN
       }
       loss_param {
           ignore_label: 255
       }
       focal_loss_param {
           alpha: 0.25
           gamma: 2.00
       }
   }