update app.py

app.py

@@ -0,0 +1,22 @@
+import tensorflow as tf
+
+inception_net = tf.keras.applications.MobileNetV2()
+
+import requests
+
+# Download human-readable labels for ImageNet.
+response = requests.get("https://git.io/JJkYN")
+labels = response.text.split("\n")
+
+def classify_image(inp):
+    inp = inp.reshape((-1, 224, 224, 3))
+    inp = tf.keras.applications.mobilenet_v2.preprocess_input(inp)
+    prediction = inception_net.predict(inp).flatten()
+    confidences = {labels[i]: float(prediction[i]) for i in range(1000)}
+    return confidences
+    
+gr.Interface(fn=classify_image, 
+             inputs=gr.Image(shape=(224, 224)),
+             outputs=gr.Label(num_top_classes=3),
+             #examples=["banana.jpg", "car.jpg"]
+            ).launch(share=True)