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