supposed to solve https://github.com/qurator-spk/sbb_binarization/issues/41

build_model_load_pretrained_weights_and_save.py

@@ -0,0 +1,33 @@
+import os
+import sys
+import tensorflow as tf
+import keras , warnings
+from keras.optimizers import *
+from sacred import Experiment
+from models import *
+from utils import *
+from metrics import *
+
+
+    
+    
+def configuration():
+    gpu_options = tf.compat.v1.GPUOptions(allow_growth=True)
+    session = tf.compat.v1.Session(config=tf.compat.v1.ConfigProto(gpu_options=gpu_options))
+
+
+if __name__=='__main__':
+    n_classes = 2
+    input_height = 224
+    input_width = 448
+    weight_decay = 1e-6
+    pretraining = False
+    dir_of_weights = 'model_bin_sbb_ens.h5'
+    
+    #configuration()
+    
+    model = resnet50_unet(n_classes,  input_height, input_width,weight_decay,pretraining)
+    model.load_weights(dir_of_weights)
+    model.save('./name_in_another_python_version.h5')
+    
+