Update app.py

app.py

@@ -3,14 +3,16 @@ import tensorflow as tf
 import numpy as np
 from PIL import Image, ImageOps
 import socket
+
 def find_free_port():
     with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s:
-        s.bind(('', 0))  # Bind to a free port assigned by the OS
+        s.bind(('', 0))
         return s.getsockname()[1]
 
 free_port = find_free_port()
 print(f"Launching Gradio on free port: {free_port}")
-# Load model (upload best_cnnmodel.h5 alongside this script)
+
+# Make sure this filename is correct!
 model = tf.keras.models.load_model('best_cnnmodelf&n.h5')
 
 class_names = ['glioma_tumor', 'meningioma_tumor', 'no_tumor', 'pituitary_tumor']
@@ -18,8 +20,8 @@ class_names = ['glioma_tumor', 'meningioma_tumor', 'no_tumor', 'pituitary_tumor'
 def preprocess(image):
     size = (150, 150)
     image = ImageOps.fit(image, size, Image.ANTIALIAS)
-    image = np.array(image) / 255.0  # Normalize to 0-1
-    image = np.expand_dims(image, axis=0)  # Add batch dimension
+    image = np.array(image) / 255.0
+    image = np.expand_dims(image, axis=0)
     return image
 
 def classify(image):
@@ -31,25 +33,20 @@ def classify(image):
     confidence = scores[top_idx] * 100
     return f"Prediction: {predicted_class}", f"Confidence: {confidence:.2f}%"
 
-# Create Gradio interface
-title = "Brain Tumor Classification"
-description = """
+iface = gr.Interface(
+    fn=classify,
+    inputs=gr.Image(type="pil", label="Upload MRI scan"),
+    outputs=[gr.Textbox(label="Prediction"), gr.Textbox(label="Confidence")],
+    title="Brain Tumor Classification",
+    description="""
 Upload a brain MRI scan image (jpg or png). The model will classify the tumor type as:
 - Glioma Tumor
 - Meningioma Tumor
 - No Tumor
 - Pituitary Tumor
-"""
-
-iface = gr.Interface(
-    fn=classify,
-    inputs=gr.Image(type="pil", label="Upload MRI scan"),
-    outputs=[gr.Textbox(label="Prediction"), gr.Textbox(label="Confidence")],
-    title=title,
-    description=description,
+""",
     allow_flagging="never",
 )
 
 if __name__ == "__main__":
-    iface.launch()
-
+    iface.launch(server_port=free_port)