Update app.py

app.py

@@ -3,14 +3,24 @@ import tensorflow as tf
 from PIL import Image
 import numpy as np
  
-labels = ['Ditto','Golbat','Koffing']
+labels = ['barrel_jellyfish',
+
+'blue_jellyfish',
+
+'compass_jellyfish'
+
+'lions_mane_jellyfish',
+
+'mauve_stinger_jellyfish',
+
+'Moon_jellyfish']
  
-def predict_pokemon_type(uploaded_file):
+def predict_jellyfish_type(uploaded_file):
     
     if uploaded_file is None:
         return "No file uploaded."
    
-    model = tf.keras.models.load_model('Ditto-premiumdelux-model_transferlearning.keras')
+    model = tf.keras.models.load_model('Jellyfish_InceptionResNetV2_transferlearning.keras')
     # Load the image from the file path
     with Image.open(uploaded_file) as img:
         img = img.resize((150, 150)).convert('RGB')  # Convert image to RGB
@@ -24,11 +34,11 @@ def predict_pokemon_type(uploaded_file):
  
 # Define the Gradio interface
 iface = gr.Interface(
-    fn=predict_pokemon_type,  # Function to process the input
+    fn=predict_jellyfish_type,  # Function to process the input
     inputs=gr.File(label="Upload File"),  # File upload widget
     outputs="text",  # Output type
-    title="Pokemon Classifier",  # Title of the interface
-    description="Upload a picture of a pokemon (preferably Ditto, Golbat, Koffing)"  # Description of the interface
+    title="Jellifish Classifier",  # Title of the interface
+    description="Upload a picture of a Jellyfish (preferably barrel, blue, compass, lions mane, mauve stinger, Moon)"  # Description of the interface
 )
  
 # Launch the interface