Update app.py

app.py

@@ -5,9 +5,25 @@ import numpy as np
 from PIL import Image
 import base64
 
-# Load the pre-trained brain tumor segmentation model
-model = tf.keras.models.load_model("model.h5")
-img_size = (256, 256)  # Adjust based on your model's input size
+H = 256
+W = 256
+smooth = 1e-15
+
+def dice_loss(y_true, y_pred):
+    y_true = tf.keras.layers.Flatten()(y_true)
+    y_pred = tf.keras.layers.Flatten()(y_pred)
+    intersection = tf.reduce_sum(y_true * y_pred)
+    return 1.0 - (2. * intersection + smooth) / (tf.reduce_sum(y_true) + tf.reduce_sum(y_pred) + smooth)
+
+def dice_coef(y_true, y_pred):
+    y_true = tf.keras.layers.Flatten()(y_true)
+    y_pred = tf.keras.layers.Flatten()(y_pred)
+    intersection = tf.reduce_sum(y_true * y_pred)
+    return (2. * intersection + smooth) / (tf.reduce_sum(y_true) + tf.reduce_sum(y_pred) + smooth)
+
+model_path = "model.h5"
+
+model = tf.keras.models.load_model(model_path,custom_objects={'dice_loss': dice_loss, 'dice_coef': dice_coef})
 
 st.set_page_config(
     page_title="Brain Tumor Segmentation App",
@@ -28,12 +44,9 @@ custom_style = """
     }
 </style>
 """
-
 st.markdown(custom_style, unsafe_allow_html=True)
 
 
-
-
 def main():
     st.title("Brain Tumor Segmentation App")