Freeze Existing ML Model to Unity 3d Python Code

freeze.py

# IMPORTS

import tensorflow as tf
# freeze_graph "screenshots" the graph
from tensorflow.python.tools import freeze_graph
# optimize_for_inference lib optimizes this frozen graph
from tensorflow.python.tools import optimize_for_inference_lib

# os and os.path are used to create the output file where we save our frozen graphs
import os
import os.path as path


MODEL_NAME = '8_OCR'
input_graph_path = '/Users/shubhrasarker/Desktop/OCR/PBAR/OCRModel/'+ MODEL_NAME+'.pbtx'
checkpoint_path = '/Users/shubhrasarker/Desktop/OCR/PBAR/OCRModel/'+MODEL_NAME+'.ckpt'
    # an arbitrary name for our graph
GRAPH_NAME = MODEL_NAME +'frozen_unity'


    # GRAPH SAVING - '.bytes'
    # freeze_graph.freeze_graph(input_graph_path, input_saver_def_path,
                           # input_binary, checkpoint_path, output_node_names,
                           # restore_op_name, filename_tensor_name,
                           # output_frozen_graph_name, clear_devices, "")
freeze_graph.freeze_graph(input_graph_path, None, False, checkpoint_path, "y_pred",
                        "save/restore_all", "save/Const:0",
                        '/Users/shubhrasarker/Desktop/OCR/PBAR/OCRModel/frozen_' + GRAPH_NAME + '.bytes', True, "")


print("graph saved!")