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import gradio as gr
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import tensorflow as tf
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model_0 = tf.keras.models.load_model('bestmodel_porno_final_meilleure100%2.0.h5')
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def classify_image(inp):
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inp = inp.reshape((-1, 224, 224, 3))
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prediction = model_0.predict(inp)
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if prediction.argmax() == 0:
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output = "Rifle violence"
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elif prediction.argmax() == 1:
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output = "guns violence"
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elif prediction.argmax() == 2:
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output = "knife violence"
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elif prediction.argmax() == 3:
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output = "image porno"
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elif prediction.argmax() == 4:
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output = "personne habillée"
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else:
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output = "tank violence"
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return output
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image = gr.inputs.Image(shape=(224, 224))
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label = gr.outputs.Label(num_top_classes=3)
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gr.Interface(
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fn=classify_image, inputs=image, outputs=label, interpretation="default"
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).launch()
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