def CreateGraph(self, model, model_width, model_height, dvpp_width,
dvpp_height):
myGraph = hiai.hiai._global_default_graph_stack.get_default_graph()
if myGraph is None:
print
'get defaule graph failed'
return None
cropConfig = hiai.CropConfig(0, 0, dvpp_width, dvpp_height)
print 'cropConfig ', cropConfig
resizeConfig = hiai.ResizeConfig(model_width, model_height)
print 'resizeConfig ', resizeConfig
nntensorList = hiai.NNTensorList()
print 'nntensorList', nntensorList
resultCrop = hiai.crop(nntensorList, cropConfig)
print 'resultCrop', resultCrop
resultResize = hiai.resize(resultCrop, resizeConfig)
print 'resultResize', resultResize
resultInference = hiai.inference(resultResize, model, None)
print 'resultInference', resultInference
if (hiai.HiaiPythonStatust.HIAI_PYTHON_OK == myGraph.create_graph()):
print 'create graph ok !!!!'
return myGraph
else:
print 'create graph failed, please check Davinc log.'
return None
def CreateGraph(model):
# Get default graph, then arrange the pipeline
myGraph = hiai.hiai._global_default_graph_stack.get_default_graph()
if myGraph is None:
print("[ERROR] Fail to get default graph.")
return None
nnTensorList = hiai.NNTensorList()
hiai.inference(nnTensorList, model, None)
if hiai.HiaiPythonStatust.HIAI_PYTHON_OK == myGraph.create_graph():
print("[OK] Finish creating graph.")
return myGraph
else:
print("[ERROR] Fail to create graph, please check Davinc log.")
return None
def CreateGraph(model):
#调用get_default_graph获取默认Graph，再进行流程编排
myGraph = hiai.hiai._global_default_graph_stack.get_default_graph()
if myGraph is None:
print('get defaule graph failed')
return None
nntensorList = hiai.NNTensorList()
resultInference = hiai.inference(nntensorList, model, None)
if (hiai.HiaiPythonStatust.HIAI_PYTHON_OK == myGraph.create_graph()):
print('create graph ok !')
return myGraph
else:
print('create graph failed, please check Davinc log.')
return None
def CreateGraphWithoutDVPP(self, model):
myGraph = hiai.hiai._global_default_graph_stack.get_default_graph()
if myGraph is None:
print 'get defaule graph failed'
return None
nntensorList = hiai.NNTensorList()
if nntensorList is None:
print('nntensor is None')
return None
resultInference = hiai.inference(nntensorList, model, None)
if (hiai.HiaiPythonStatust.HIAI_PYTHON_OK == myGraph.create_graph()):
print 'create graph ok !!!!'
return myGraph
else:
print 'create graph failed!'
return None
def CreateGraph(model):
# 调用get_default_graph获取默认Graph，再进行流程编排
myGraph = hiai.hiai._global_default_graph_stack.get_default_graph()
if myGraph is None:
print 'Get default graph failed'
return None
nntensorList = hiai.NNTensorList()
# 不实用DVPP缩放图像，使用opencv缩放图片
resultInference = hiai.inference(nntensorList, model, None) # 不确定其功能
if (hiai.HiaiPythonStatust.HIAI_PYTHON_OK == myGraph.create_graph()):
print 'create graph ok !'
return myGraph
else:
print 'create graph failed, please check log.'
return None
def CreateGraph(self, model):
# 获取Graph实例
myGraph = hiai.hiai._global_default_graph_stack.get_default_graph()
if myGraph is None:
print('get defaule graph failed')
return None
# 初始化Engine,配置推理算子(加载模型)
# API固定调用流程
nntensorList = hiai.NNTensorList()
if (None == hiai.inference(nntensorList, model, None)):
print('Init Engine failed !!!!')
return None
else:
print('Init Engine ok!')
# 创建推理接口
if (hiai.HiaiPythonStatust.HIAI_PYTHON_OK == myGraph.create_graph()):
print('create graph ok !!!!')
return myGraph
else:
print('create graph failed!')
return None
def CreateGraphWithoutDVPP(model):
print model
myGraph = hiai.hiai._global_default_graph_stack.get_default_graph()
print myGraph
if myGraph is None:
print 'get defaule graph failed'
return None
nntensorList = hiai.NNTensorList()
print nntensorList
resultInference = hiai.inference(nntensorList, model, None)
print nntensorList
print hiai.HiaiPythonStatust.HIAI_PYTHON_OK
#print myGraph.create_graph()
if (hiai.HiaiPythonStatust.HIAI_PYTHON_OK == myGraph.create_graph()):
print 'create graph ok !!!!'
return myGraph
else:
print 'create graph failed, please check Davinc log.'
return None