Gradio interface for testing the model

app.py

@@ -0,0 +1,27 @@
+import tensorflow as tf
+import gradio as gr
+
+model = tf.keras.models.load_model('model.h5')
+
+def recognize_digit(image):
+    if image is not None:
+        image = image.reshape((1, 28, 28, 1)) / 255.0
+        prediction = model.predict(image)
+        
+        return {str(i): float(prediction[0][i]) for i in range(10)}
+    else:
+        return ''
+
+iface = gr.Interface(
+    fn=recognize_digit,
+    inputs=gr.Image(
+        shape=(28, 28),
+        image_mode='L',
+        invert_colors=True,
+        source='canvas'
+    ),
+    outputs=gr.Label(num_top_classes=3),
+    live=True
+)
+
+iface.launch(share=True)