updated app.py

app.py

@@ -11,48 +11,34 @@ from sklearn.preprocessing import OneHotEncoder
 import pickle
 import gradio as gr
 
-def load_model():
-    save_path = 'model_architecture.json'
-    with open(save_path, 'r') as file:
-        model = keras.models.model_from_json(file.read())
-    model.load_weights('model_weights.h5')
-    return model
+# Load the model
+model_path = "model.pkl"
+model = tf.keras.models.load_model(model_path)
 
-def predict_dementia(images, model):
-    predictions = []
-    for image in images:
-        img = Image.fromarray(image.astype('uint8'))
-        img = img.resize((128, 128))
-        img = np.array(img)
-        img = img.reshape(1, 128, 128, 3)
-        
-        prediction = model.predict(img)
-        prediction_class = np.argmax(prediction)
-        predictions.append(names(prediction_class))
-    return predictions
+# Define the labels
+labels = ['Non Demented', 'Mild Dementia', 'Moderate Dementia', 'Very Mild Dementia']
 
-def names(number):
-    if number == 0:
-        return 'Non Demented'
-    elif number == 1:
-        return 'Mild Dementia'
-    elif number == 2:
-        return 'Moderate Dementia'
-    elif number == 3:
-        return 'Very Mild Dementia'
-    else:
-        return 'Error in Prediction'
+# Define the prediction function
+def predict_dementia(image):
+    img = Image.fromarray(image.astype('uint8'))
+    img = img.resize((128, 128))
+    img = np.array(img)
+    img = img.reshape(1, 128, 128, 3)
+    
+    prediction = model.predict(img)
+    prediction_class = np.argmax(prediction)
+    return labels[prediction_class]
 
-def main(images):
-    model = load_model()
-    predictions = predict_dementia(images, model)
-    return predictions
+# Create the Gradio interface
+iface = gr.Interface(
+    fn=predict_dementia,
+    inputs="image",
+    outputs="text",
+    title="Dementia Classification",
+    description="Classify dementia based on brain images",
+    examples=[["Non(1).jpg"],["Mild.jpg"],["Moderate.jpg"],["Very(1).jpg"]],
+    allow_flagging=False
+)
 
-iface = gr.Interface(fn=main,
-                     inputs="image",
-                     outputs="text",
-                     title="Dementia Classification",
-                     description="Classify dementia based on brain images",
-                     examples=[["Non(1).jpg"],["Moderate.jpg"],["Mild.jpg"]])
-
-iface.launch(debug =True)
+# Launch the interface
+iface.launch(debug=True)