Update app.py

app.py

@@ -20,19 +20,15 @@ img_size = 28
 
 labels = ["zero", "one", "two", "three", "four", "five", "six", "seven", "eight", "nine"]
 
-# Tahmin fonksiyonu
 def predict(img):
     try:
-        # If the input is a dictionary (Gradio sketchpad), extract the image
-        if isinstance(img, dict):
-            img = img.get('image', None)  # Get the image from the dictionary
-
-        if img is None:
-            raise ValueError("No image data found")
+        # Check if the image is a PIL object and convert it to NumPy array
+        if isinstance(img, Image.Image):
+            img = np.array(img)
 
-        # Convert the input image to a NumPy array if needed
+        # If the input is still not a NumPy array, return an error
         if not isinstance(img, np.ndarray):
-            img = np.array(img)
+            raise ValueError("Input is not a valid image")
 
         # Print shape and type of the input image
         print(f"Initial image type: {type(img)}, shape: {img.shape}")
@@ -69,6 +65,8 @@ def predict(img):
         print(f"Error during prediction: {e}")
         return {"Error": str(e)}
 
+   
+
 # Set up the Gradio interface with the input as a sketchpad and output as labels
 label = gr.Label(num_top_classes=3)
 
@@ -81,4 +79,4 @@ interface = gr.Interface(
     description="Draw a number (0-9) and see the model's top predictions."
 )
 
-interface.launch(debug=True)
+interface.launch(debug=True, share=True)