Update app.py

app.py

@@ -8,7 +8,7 @@ from tensorflow.keras.models import load_model
 import os
 
 os.system('wget -O model.h5 "https://drive.google.com/u/0/uc?id=1UqXYR2e3c0VW8Ax4nYLvef7Vmlx3AEGi&export=download"')
-os.system('wget -O model2.pkl "https://drive.google.com/u/0/uc?id=16FuBwWEhG7oHH2YGm8EkEDTbv6GSUbyg&export=download"')
+os.system('wget -O model2.pkl "https://drive.google.com/u/0/uc?id=1avoaq0fNGrLb4JatN0C-3rL8VnX2x4Ch&export=download"')
 
 # Load the RGB to hyperspectral conversion model
 #converion_model = load_model('/kaggle/input/convmo/Conversion_model.h5')
@@ -35,10 +35,10 @@ def classify(rgb_image):
     imgplot = hyperspectral_image.numpy().astype(np.float32)
     imgplot= imgplot.reshape(-1, 272*512*16)
     prediction = cancer_model.predict(imgplot)
-    if np.argmax(prediction) == 0:
-        x= "cancer"
+    if prediction == 0:
+         x= "High Risk of being a Cancerous Mole"
     else:
-        x="not a cancer"
+         x="Normal mole"
     return x  
 
 # Define the Gradio interface