Add application file

app.py

@@ -1,8 +1,9 @@
 import tensorflow as tf
 import requests
 import gradio as gr
+import numpy as np
 
-# Load the InceptionNet model
+# Load the MobileNetV2 model
 inception_net = tf.keras.applications.MobileNetV2(weights="imagenet")
 
 # Download human-readable labels for ImageNet
@@ -14,7 +15,7 @@ def classify_image(image):
     # Preprocess the user-uploaded image
     image = tf.image.resize(image, [224, 224])
     image = tf.keras.applications.mobilenet_v2.preprocess_input(image)
-    image = tf.expand_dims(image, axis=0)
+    image = np.expand_dims(image, axis=0)
 
     # Make predictions using the MobileNetV2 model
     prediction = inception_net.predict(image).flatten()
@@ -29,12 +30,12 @@ def classify_image(image):
 # Create the Gradio interface
 iface = gr.Interface(
     fn=classify_image,
-    inputs=gr.inputs.Image(shape=(224, 224)),
-    outputs=gr.outputs.Label(num_top_classes=3),
+    inputs=gr.Image(shape=(224, 224)),
+    outputs=gr.Label(num_top_classes=3),
     live=True,
     title="Image Classification",
     description="Upload an image, and the model will classify it into the top 3 categories.",
 )
 
 # Launch the Gradio interface
-iface.launch()
+iface.launch()

requirements.txt

@@ -1,3 +1,4 @@
 tensorflow
 requests
-gradio
+gradio
+numpy