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import tensorflow as tf
import requests
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()
confidences = {labels[i]: float(prediction[i]) for i in range(1000)}
return confidences
gr.Interface(fn=classify_image, inputs = gr.inputs.Image(shape = (224, 244)), outputs = gr.outputs.Label(num_top_classes=5)).launch()
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