Create app.py

app.py

@@ -0,0 +1,14 @@
+import numpy as np
+import pandas as pd
+import matplotlib.pyplot as plt
+
+from tensorflow.keras.applications import ResNet50V2
+from tensorflow.keras.models import Sequential, load_model
+from tensorflow.keras.layers import Dense
+from tensorflow.keras.utils import to_categorical
+from tensorflow.keras.applications.resnet_v2 import preprocess_input
+from tensorflow.keras.preprocessing.image import load_img, img_to_array
+
+model = load_model('my_cnn_model.h5') # Loading the Tensorflow Saved Model (PB)
+print(model.summary())
+