Inference on tensorflow 2.x

test_code/cartoonize.py

@@ -1,7 +1,11 @@
+try:
+    import tensorflow.compat.v1 as tf
+except ImportError:
+    import tensorflow as tf
+
 import os
 import cv2
 import numpy as np
-import tensorflow as tf 
 import network
 import guided_filter
 from tqdm import tqdm
@@ -23,6 +27,13 @@ def resize_crop(image):
 
 
 def cartoonize(load_folder, save_folder, model_path):
+    try:
+        tf.disable_eager_execution()
+    except:
+        None
+
+    tf.reset_default_graph()
+
     input_photo = tf.placeholder(tf.float32, [1, None, None, 3])
     network_out = network.unet_generator(input_photo)
     final_out = guided_filter.guided_filter(input_photo, network_out, r=1, eps=5e-3)
@@ -63,6 +74,3 @@ def cartoonize(load_folder, save_folder, model_path):
     if not os.path.exists(save_folder):
         os.mkdir(save_folder)
     cartoonize(load_folder, save_folder, model_path)
-
-
-

test_code/guided_filter.py

@@ -1,4 +1,8 @@
-import tensorflow as tf
+try:
+    import tensorflow.compat.v1 as tf
+except ImportError:
+    import tensorflow as tf
+
 import numpy as np
 
 

test_code/network.py

@@ -1,6 +1,11 @@
-import tensorflow as tf
+try:
+    import tensorflow.compat.v1 as tf
+    import tf_slim as slim
+except ImportError:
+    import tensorflow as tf
+    import tensorflow.contrib.slim as slim
+
 import numpy as np
-import tensorflow.contrib.slim as slim
 
 
 
@@ -59,4 +64,4 @@ def unet_generator(inputs, channel=32, num_blocks=4, name='generator', reuse=Fal
 if __name__ == '__main__':
 
 
-    pass
+    pass