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import tensorflow as tf
import requests
import gradio as gr
inception_net = tf.keras.applications.MobileNetV2()
# Obteniendo las labels de "https://git.io/JJkYN"
respuesta = requests.get("https://git.io/JJkYN")
etiquetas = respuesta.text.split("\n")
def clasifica_imagen(inp):
inp = inp.reshape((-1, 224, 224, 3))
inp = tf.keras.applications.mobilenet_v2.preprocess_input(inp)
prediction = inception_net.predict(inp).flatten()
confidences = {etiquetas[i]: float(prediction[i]) for i in range(1000)}
return confidences
demo = gr.Interface(fn=clasifica_imagen,
inputs=gr.Image(shape=(224, 224)),
outputs=gr.Label(num_top_classes=3)
)
demo.launch() |