Update app.py

app.py

@@ -2,16 +2,20 @@ from huggingface_hub import from_pretrained_keras
 import gradio as gr 
 import tensorflow as tf 
 import numpy as np 
+import os
 
-model = from_pretrained_keras("keras-io/semantic-segmentation")
+model = tf.keras,models.load.model(os.path.join 
 
 inputs = gr.inputs.Image()
 output = gr.output.Image()
 
 
 def predict(image_input):
+    img = np.array(inputs)
+    
   pass 
-  
+
+
 class PreTrainedPipeline():
     def __init__(self, path: str):
         # load the model
@@ -58,7 +62,7 @@ class PreTrainedPipeline():
                         binary_masks[f"mask_{cls}"][row][col] = 0
 
             mask = binary_masks[f"mask_{cls}"]
-            mask *= 255
+            mask *= 255 
             img = Image.fromarray(mask.astype(np.int8), mode="L")
                
             # we need to make it readable for the widget
@@ -68,4 +72,12 @@ class PreTrainedPipeline():
                 mask = base64.b64encode(png_string).decode("utf-8")
 
             mask_codes[f"mask_{cls}"] = mask
+    
 
+            # widget needs the below format, for each class we return label and mask string
+            labels.append({
+                "label": f"LABEL_{cls}",
+                "mask": mask_codes[f"mask_{cls}"],
+                "score": 1.0,
+            })
+        return labels