Update app.py

app.py

@@ -18,8 +18,6 @@ import matplotlib.pyplot as plt
 from matplotlib.colors import LinearSegmentedColormap
 import textwrap
 import plotly.graph_objects as go
-from tensorflow.keras.applications.efficientnet import preprocess_input
-
 
 st.set_page_config(
     page_title="Food Chain", 
@@ -232,17 +230,19 @@ class_names = [
 
 def classifyImage(input_image):
     input_image = input_image.resize((img_size, img_size))
-    input_array = tf.keras.utils.img_to_array(input_image)
+    input_array = tf.keras.utils.img_to_array(input_image) / 255.0
 
     # Add a batch dimension 
     input_array = tf.expand_dims(input_array, 0)  # (1, 224, 224, 3)
-    input_array = preprocess_input(input_array) #TESTING
 
     predictions = model.predict(input_array)[0]
     print(f"Predictions: {predictions}")
     predictions = tf.nn.softmax(predictions).numpy() #TESTING
     print(f"Predictions AFTER SOFTMAX: {predictions}")
-
+    
+    probability_sum = predictions.sum() * 100
+    print(f"Sum of predictions (as percentages): {probability_sum:.2f}%")
+    
     # Sort predictions to get top 5
     top_indices = np.argsort(predictions)[-5:][::-1]