@ -270,12 +270,12 @@ def createSSDGraph(modelPath, configPath, outputPath):
addConstNode ( ' concat/axis_flatten ' , [ - 1 ] , graph_def )
addConstNode ( ' concat/axis_flatten ' , [ - 1 ] , graph_def )
addConstNode ( ' PriorBox/concat/axis ' , [ - 2 ] , graph_def )
addConstNode ( ' PriorBox/concat/axis ' , [ - 2 ] , graph_def )
for label in [ ' ClassPredictor ' , ' BoxEncodingPredictor ' if box_predictor is ' convolutional ' else ' BoxPredictor ' ] :
for label in [ ' ClassPredictor ' , ' BoxEncodingPredictor ' if box_predictor == ' convolutional ' else ' BoxPredictor ' ] :
concatInputs = [ ]
concatInputs = [ ]
for i in range ( num_layers ) :
for i in range ( num_layers ) :
# Flatten predictions
# Flatten predictions
flatten = NodeDef ( )
flatten = NodeDef ( )
if box_predictor is ' convolutional ' :
if box_predictor == ' convolutional ' :
inpName = ' BoxPredictor_ %d / %s /BiasAdd ' % ( i , label )
inpName = ' BoxPredictor_ %d / %s /BiasAdd ' % ( i , label )
else :
else :
if i == 0 :
if i == 0 :
@ -308,7 +308,7 @@ def createSSDGraph(modelPath, configPath, outputPath):
priorBox = NodeDef ( )
priorBox = NodeDef ( )
priorBox . name = ' PriorBox_ %d ' % i
priorBox . name = ' PriorBox_ %d ' % i
priorBox . op = ' PriorBox '
priorBox . op = ' PriorBox '
if box_predictor is ' convolutional ' :
if box_predictor == ' convolutional ' :
priorBox . input . append ( ' BoxPredictor_ %d /BoxEncodingPredictor/BiasAdd ' % i )
priorBox . input . append ( ' BoxPredictor_ %d /BoxEncodingPredictor/BiasAdd ' % i )
else :
else :
if i == 0 :
if i == 0 :