Update app.py

app.py

@@ -1,6 +1,3 @@
-import os
-os.environ["SM_FRAMEWORK"] = "tf.keras"
-
 import os
 import cv2
 from PIL import Image 
@@ -27,7 +24,9 @@ dice_loss = sm.losses.DiceLoss(class_weights = weights)
 focal_loss = sm.losses.CategoricalFocalLoss()
 total_loss = dice_loss + (1 * focal_loss) 
 
-satellite_model = load_model('C:/Users/sa/Desktop/Model_Training/satellite_segmentation_full.h5', custom_objects={'dice_loss_plus_1focal_loss': total_loss})
+satellite_model = load_model('C:/Users/sa/Desktop/Model_Training/satellite_segmentation_full.h5',
+                         custom_objects=({'dice_loss_plus_1focal_loss': total_loss, 
+                                          'jaccard_coef': jaccard_coef}))
 
 
 def process_input_image(image_source):
@@ -44,8 +43,8 @@ my_app = gr.Blocks()
 
 with my_app:
   gr.Markdown("Statellite Image Segmentation Application UI with Gradio")
-  with gr.Tabs():      
-    with gr.TabItem ("Select your image"):
+  with gr.Tabs():
+    with gr.TabItem("Select your image"):
       with gr.Row():
         with gr.Column():
             img_source = gr.Image(label="Please select source Image", shape=(256, 256))
@@ -54,14 +53,15 @@ with my_app:
             output_label = gr.Label(label="Image Info")
             img_output = gr.Image(label="Image Output")
     source_image_loader.click(
-      process_input_image,
-      [
-        img_source
-      ],
-      [
-        output_label,
-        img_output
-      ]
+        process_input_image,
+        [
+            img_source
+        ],
+        [
+            output_label,
+            img_output
+        ]
     )
 
+
 my_app.launch(debug=True)