hi fixed

app.py

@@ -5,36 +5,35 @@ from PIL import Image
 
 MODEL_PATH = "mnist_cnn.h5"
 
-# Load model (CPU only – CUDA warnings are normal)
 model = tf.keras.models.load_model(MODEL_PATH)
 
 
 def preprocess(image):
-    # image arrives as numpy array (H, W, C)
     if image is None:
         return None
 
-    # Convert to PIL
-    image = Image.fromarray(image.astype("uint8"))
+    # Ensure PIL
+    if isinstance(image, np.ndarray):
+        image = Image.fromarray(image.astype("uint8"))
 
     # Convert to grayscale
     image = image.convert("L")
 
-    # Resize to MNIST
+    # Resize
     image = image.resize((28, 28))
 
     img = np.array(image).astype("float32")
 
-    # Invert colors (MNIST = white digit on black)
+    # Invert colors (MNIST style)
     img = 255 - img
 
-    # Threshold to remove gray noise
+    # Remove background noise
     img[img < 40] = 0
 
     # Normalize
     img /= 255.0
 
-    # Add channel & batch dimensions
+    # Add dims
     img = np.expand_dims(img, axis=-1)
     img = np.expand_dims(img, axis=0)
 
@@ -47,22 +46,20 @@ def predict(image):
     return {str(i): float(preds[i]) for i in range(10)}
 
 
-with gr.Blocks() as demo:
-    gr.Markdown("# ✍️ MNIST Handwritten Digit Classifier")
-    gr.Markdown("Draw a **single large digit**, centered, like MNIST.")
-
-    canvas = gr.Image(
-        label="Draw a digit",
-        tool="sketch",          # ✅ correct canvas for Gradio 4.x
-        image_mode="RGB",
-        height=280,
-        width=280
-    )
-
-    output = gr.Label(num_top_classes=3)
-
-    btn = gr.Button("Predict")
-
-    btn.click(fn=predict, inputs=canvas, outputs=output)
+demo = gr.Interface(
+    fn=predict,
+    inputs=gr.Image(
+        label="Upload a digit image (white digit on dark background)"
+    ),
+    outputs=gr.Label(num_top_classes=3),
+    title="MNIST Handwritten Digit Classifier",
+    description=(
+        "Upload an image of a handwritten digit.\n\n"
+        "Tips:\n"
+        "- Dark background\n"
+        "- Light digit\n"
+        "- Centered and large"
+    ),
+)
 
 demo.launch()

requirements.txt

@@ -1,4 +1,4 @@
 tensorflow>=2.11
 numpy
 pillow
-gradio>=4.0
+gradio