Upload app.py

app.py

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+import tensorflow as tf
+import gradio as gr
+import numpy as npd
+from PIL import Image
+
+
+loaded_model = tf.keras.models.load_model('digit_recognition_model.h5')
+
+def recognize_digit(image):
+    # Preprocess the input image
+    image = Image.fromarray(image).convert('L')  # Convert to grayscale
+    image = image.resize((28, 28))  # Resize to 28x28
+    image = np.array(image)
+    image = image / 255.0  # Normalize the pixel values
+
+    # Make a prediction using the loaded model
+    image = np.expand_dims(image, axis=0)  # Add a batch dimension
+    prediction = loaded_model.predict(image)
+    predicted_digit = np.argmax(prediction)
+
+    return str(predicted_digit)
+
+iface = gr.Interface(fn=recognize_digit, inputs="image", outputs="text")
+iface.launch(share = True)