Get the test runner operating again.

Models/model_testrunner.py

@@ -1,11 +1,11 @@
-import sys
-import os
-import glob
+# import sys
+# import os
+# import glob
 
-from keras.layers.pooling import MaxPool2D 
+# from keras.layers.pooling import MaxPool2D 
 
-sys.path.append('c:/git/keras')
-sys.path.append('c:/git/absl')
+# sys.path.append('c:/git/keras')
+# sys.path.append('c:/git/absl')
 
 # installed 
 # py -mpip install numpy
@@ -15,15 +15,34 @@ sys.path.append('c:/git/absl')
 # py -mpip install matplotlib
 # c:\users\skess\appdata\local\programs\python\python39\lib\site-packages
 
-import keras
-from keras.preprocessing.image import ImageDataGenerator
-import numpy as np
-import tensorflow
+# import keras
+# from keras.preprocessing.image import ImageDataGenerator
+# import numpy as np
+# import tensorflow
 
 #model_name='lenet5.h5'
+
+import sys
+import os
+import glob
+from keras.optimizers import SGD
+from keras.optimizers import Adam
+from tensorflow.keras.callbacks import TensorBoard
+import keras
+from keras.src.legacy.preprocessing.image import ImageDataGenerator
+from keras.callbacks import ModelCheckpoint
+from tensorflow.keras.callbacks import EarlyStopping
+import numpy as np
+import tensorflow
+from resnet50 import *
+import math
+from time import time
+
+
 print(os.getcwd())
 
-model_name='../Weights/resnet50.h5'
+path = os.getcwd()
+model_name='Weights/resnet50_20241024_270.h5.keras'
 
 # *************************************************** T E S T I N G ********************************************
 
@@ -49,7 +68,10 @@ model_name='../Weights/resnet50.h5'
 
 # Load the model
 
-model = keras.models.load_model(model_name)
+real_path = os.path.realpath(path + '/' + model_name)
+
+print('Loading {model_name}'.format(model_name=real_path))
+model = keras.models.load_model(real_path)
 
 # image_path='C:/boneyard/DeepLearning/IndividualValidationCases/SIG_0_Test_BollingerBand.jpg'
 # test_image = tensorflow.keras.preprocessing.image.load_img(image_path,color_mode='grayscale')
@@ -72,8 +94,6 @@ model = keras.models.load_model(model_name)
 files=glob.glob("C:/boneyard/DeepLearning/IndividualValidationCases/*.jpg")
 #files=glob.glob("C:/boneyard/DeepLearning/data/VolatilityPriceContraction/*.jpg")
 
-
-
 for file in files:
     test_image = tensorflow.keras.preprocessing.image.load_img(file,color_mode='grayscale')
     test_array = keras.preprocessing.image.img_to_array(test_image)