Update app.py

app.py

@@ -17,8 +17,14 @@ with open(config_path, "r", encoding="utf-8") as f:
 # Initialize the pipeline
 pipe = pipeline(task="image-classification", model=model_repo)
 
+# Define a custom prediction function
+import numpy as np
+
 # Define a custom prediction function
 def predict(image):
+    # Convert the image to numpy array if it's not already in that format
+    if not isinstance(image, np.ndarray):
+        raise ValueError("Input image must be a numpy array.")
     # Get the predictions from the pipeline
     predictions = pipe(image)
     # Get the predicted label index
@@ -29,6 +35,7 @@ def predict(image):
     confidence_score = predictions[0]['score']
     return f"{label_name} ({confidence_score:.2f})"
 
+
 # Create Gradio interface
 iface = gr.Interface(fn=predict,
                      inputs=gr.Image(type="numpy"),