|
import tensorflow as tf |
|
|
|
inception_net = tf.keras.applications.MobileNetV2() |
|
|
|
import requests |
|
|
|
|
|
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 |
|
|
|
import gradio as gr |
|
|
|
gr.Interface(fn=classify_image, |
|
inputs=gr.Image(width=224, height=224), |
|
outputs=gr.Label(num_top_classes=3), |
|
examples=["banana.jpg", "car.jpg"]).launch() |
