inception

app.py

@@ -1,8 +1,23 @@
-import gradio as gr
+import requests
+import tensorflow as tf
+
+inception_net = tf.keras.applications.MobileNetV2()
+
+# 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
 
-def greet(name):
-    return "Hello " + name + "!!"
 
-iface = gr.Interface(fn=greet, inputs="text", outputs="text")
-iface.launch()
+import gradio as gr
+
+gr.Interface(fn=classify_image, 
+             inputs=gr.inputs.Image(shape=(224, 224)),
+             outputs=gr.outputs.Label(num_top_classes=3),
+             examples=["banana.jpg", "car.jpg"]).launch()