Update app.py

app.py

@@ -3,11 +3,11 @@ import numpy as np
 from PIL import Image
 import gradio as gr
 
-# load your pickled RandomForest
+# load your pickled RandomForest (make sure mnist_model.pkl lives in /app)
 model = pickle.load(open("mnist_model.pkl", "rb"))
 
 def classify_digit(img: Image.Image) -> str:
-    # convert to 28×28 grayscale
+    # convert to 28×28 grayscale array
     gray = img.convert("L").resize((28, 28))
     arr = np.array(gray).reshape(1, -1)
     pred = model.predict(arr)[0]
@@ -15,10 +15,10 @@ def classify_digit(img: Image.Image) -> str:
 
 demo = gr.Interface(
     fn=classify_digit,
-    inputs=gr.inputs.Image(type="pil", label="Upload a 28×28 digit"),
-    outputs=gr.outputs.Textbox(label="Prediction"),
-    title="Digit Classifier",
-    description="Upload a handwritten MNIST digit and get a prediction!"
+    inputs=gr.Image(type="pil", label="Upload a 28×28 digit"),
+    outputs=gr.Textbox(label="Prediction"),
+    title="MNIST Digit Classifier",
+    description="Upload a handwritten digit image (28×28) to get a live prediction!"
 )
 
 if __name__ == "__main__":