feature request: export graph and invariant output names for boxes and scores about blitznet

[dvornikita]

Hi @fastlater, I really appreciate your help in debugging and developing this project.
Unfortunately, this time I can't answer the question because I don't know how to help you in this situation, at least not right now :)
I'm gonna look into the graph later, probably next week, and write you.

[fastlater]

@dvornikita Thank you for your honest answer. I will keep trying. I hope next week you have free time and check it and give me some ideas.

Update October 26,2017:
Using the code shown below, I can store the graph properly

 output_graph_def = graph_util.convert_variables_to_constants(sess,input_graph_def,output_node_names.split(","))
with tf.gfile.GFile(output_graph, "wb") as f:
                f.write(output_graph_def.SerializeToString())

optimize_for_inference.py remove some (just a few) nodes but the model is more clear in tensorboard and ready to use. Thus, blitznet can be exported using the optimize_for_inference tool.

Keep trying with tf.identity becuase simpler output nodes (1 for n locations and 1 for n scores) will make the outputs of this model easier to use when it is exported:

all_boxes = tf.identity(self.detection_list,name='all_boxes')
all_scores = tf.identity(self.score_list, name='all_scores')

However, these lines got me an error: InvalidArgumentError: Shapes of all inputs must match: values[0].shape = [0] != values[4].shape = [50]. I tried with tf.concat but then all the results found are placed in a single array and not an array of arrays. I will need help with this.