fast-reid/tools/deploy/Caffe

The Caffe in PytorchToCaffe Provides some convenient API

If there are some problem in parse your prototxt or caffemodel, Please replace the caffe.proto with your own version and compile it with command protoc --python_out ./ caffe.proto

caffe_net.py

Using from nn_tools.Caffe import caffe_net to import this model

Prototxt

• net=caffe_net.Prototxt(file_name) to open a prototxt file
• net.init_caffemodel(caffe_cmd_path='caffe') to generate a caffemodel file in the current work directory
  if your caffe cmd not in the $PATH, specify your caffe cmd path by the caffe_cmd_path kwargs.

Caffemodel

• net=caffe_net.Caffemodel(file_name) to open a caffemodel
• net.save_prototxt(path) to save the caffemodel to a prototxt file (not containing the weight data)
• net.get_layer_data(layer_name) return the numpy ndarray data of the layer
• net.set_layer_date(layer_name, datas) specify the data of one layer in the caffemodel .datas is normally a list of numpy ndarray [weights,bias]
• net.save(path) save the changed caffemodel

Functions for both Prototxt and Caffemodel

• net.add_layer(layer_params,before='',after='') add a new layer with Layer_Param object
• net.remove_layer_by_name(layer_name)
• net.get_layer_by_name(layer_name) or net.layer(layer_name) get the raw Layer object defined in caffe_pb2