| import requests |
| import tensorflow as tf |
|
|
| import gradio as gr |
|
|
| inception_net = tf.keras.applications.MobileNetV2() |
|
|
| |
| 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() |
| return {labels[i]: float(prediction[i]) for i in range(1000)} |
|
|
|
|
| image = gr.Image(shape=(224, 224)) |
| label = gr.Label(num_top_classes=3) |
|
|
| title = "Gradio Image Classifiction + Interpretation Example" |
| gr.Interface( |
| fn=classify_image, inputs=image, outputs=label, interpretation="default", title=title |
| ).launch() |
