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import requests |
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import tensorflow as tf |
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import gradio as gr |
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inception_net = tf.keras.applications.MobileNetV2() |
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response = requests.get("https://git.io/JJkYN") |
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labels = response.text.split("\n") |
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def classify_image(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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return {labels[i]: float(prediction[i]) for i in range(1000)} |
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image = gr.Image(shape=(224, 224)) |
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label = gr.Label(num_top_classes=3) |
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title="Gradio Image Classifiction + interpretation Example" |
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gr.Interface( |
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fn=classify_image, inputs=image, outputs=label, interpretation="default",title=title |
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).launch(enable_queue=False, auth=("admin", "pass1234")) |
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