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import gradio as gr
import tensorflow as tf
model_0 = tf.keras.models.load_model('bestmodel.h5')
def classify_image(inp):
inp = inp.reshape((-1, 224, 224, 3))
prediction = model_0.predict(inp)
if prediction[0][prediction.argmax()]>0.01:
if prediction.argmax() == 0:
output = "Rifle violence"
elif prediction.argmax() == 1:
output = "guns violence"
elif prediction.argmax() == 2:
output = "knife violence"
elif prediction.argmax() == 3:
output = "image porno"
elif prediction.argmax() == 4:
output = "personne habillée"
else:
output = "tank violence"
else:
output = ""
return output
image = gr.inputs.Image(shape=(224, 224))
label = gr.outputs.Label(num_top_classes=3)
gr.Interface(
fn=classify_image, inputs=image, outputs=label, interpretation="default"
).launch()
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