mirror of https://github.com/JDAI-CV/fast-reid.git
139 lines
4.6 KiB
Python
139 lines
4.6 KiB
Python
from __future__ import absolute_import
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from . import caffe_pb2 as pb
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import google.protobuf.text_format as text_format
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import numpy as np
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from .layer_param import Layer_param
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class _Net(object):
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def __init__(self):
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self.net=pb.NetParameter()
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def layer_index(self,layer_name):
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# find a layer's index by name. if the layer was found, return the layer position in the net, else return -1.
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for i, layer in enumerate(self.net.layer):
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if layer.name == layer_name:
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return i
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def add_layer(self,layer_params,before='',after=''):
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# find the before of after layer's position
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index = -1
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if after != '':
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index = self.layer_index(after) + 1
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if before != '':
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index = self.layer_index(before)
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new_layer = pb.LayerParameter()
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new_layer.CopyFrom(layer_params.param)
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#insert the layer into the layer protolist
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if index != -1:
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self.net.layer.add()
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for i in range(len(self.net.layer) - 1, index, -1):
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self.net.layer[i].CopyFrom(self.net.layer[i - 1])
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self.net.layer[index].CopyFrom(new_layer)
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else:
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self.net.layer.extend([new_layer])
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def remove_layer_by_name(self,layer_name):
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for i,layer in enumerate(self.net.layer):
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if layer.name == layer_name:
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del self.net.layer[i]
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return
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raise(AttributeError, "cannot found layer %s" % str(layer_name))
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def get_layer_by_name(self, layer_name):
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# get the layer by layer_name
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for layer in self.net.layer:
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if layer.name == layer_name:
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return layer
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raise(AttributeError, "cannot found layer %s" % str(layer_name))
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def save_prototxt(self,path):
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prototxt=pb.NetParameter()
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prototxt.CopyFrom(self.net)
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for layer in prototxt.layer:
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del layer.blobs[:]
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with open(path,'w') as f:
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f.write(text_format.MessageToString(prototxt))
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def layer(self,layer_name):
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return self.get_layer_by_name(layer_name)
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def layers(self):
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return list(self.net.layer)
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class Prototxt(_Net):
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def __init__(self,file_name=''):
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super(Prototxt,self).__init__()
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self.file_name=file_name
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if file_name!='':
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f = open(file_name,'r')
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text_format.Parse(f.read(), self.net)
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pass
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def init_caffemodel(self,caffe_cmd_path='caffe'):
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"""
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:param caffe_cmd_path: The shell command of caffe, normally at <path-to-caffe>/build/tools/caffe
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"""
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s=pb.SolverParameter()
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s.train_net=self.file_name
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s.max_iter=0
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s.base_lr=1
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s.solver_mode = pb.SolverParameter.CPU
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s.snapshot_prefix='./nn'
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with open('/tmp/nn_tools_solver.prototxt','w') as f:
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f.write(str(s))
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import os
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os.system('%s train --solver /tmp/nn_tools_solver.prototxt'%caffe_cmd_path)
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class Caffemodel(_Net):
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def __init__(self, file_name=''):
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super(Caffemodel,self).__init__()
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# caffe_model dir
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if file_name!='':
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f = open(file_name,'rb')
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self.net.ParseFromString(f.read())
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f.close()
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def save(self, path):
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with open(path,'wb') as f:
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f.write(self.net.SerializeToString())
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def add_layer_with_data(self,layer_params,datas, before='', after=''):
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"""
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Args:
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layer_params:A Layer_Param object
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datas:a fixed dimension numpy object list
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after: put the layer after a specified layer
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before: put the layer before a specified layer
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"""
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self.add_layer(layer_params,before,after)
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new_layer =self.layer(layer_params.name)
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#process blobs
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del new_layer.blobs[:]
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for data in datas:
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new_blob=new_layer.blobs.add()
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for dim in data.shape:
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new_blob.shape.dim.append(dim)
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new_blob.data.extend(data.flatten().astype(float))
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def get_layer_data(self,layer_name):
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layer=self.layer(layer_name)
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datas=[]
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for blob in layer.blobs:
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shape=list(blob.shape.dim)
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data=np.array(blob.data).reshape(shape)
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datas.append(data)
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return datas
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def set_layer_data(self,layer_name,datas):
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# datas is normally a list of [weights,bias]
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layer=self.layer(layer_name)
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for blob,data in zip(layer.blobs,datas):
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blob.data[:]=data.flatten()
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pass
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class Net():
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def __init__(self,*args,**kwargs):
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raise(TypeError,'the class Net is no longer used, please use Caffemodel or Prototxt instead') |