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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) | |
print(prediction," ",prediction.argmax()) | |
print(prediction," ",prediction.argmax()," ",prediction[prediction.argmax()]) | |
output = "" | |
if prediction[prediction.argmax()] < 0.7: | |
output = "bonne image" | |
elif 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" | |
return output | |
image = gr.inputs.Image(shape=(224, 224)) | |
gr.Interface( | |
fn=classify_image, inputs=image, outputs="text",live=True, theme="dark-peach",title="API de détection des images violentes", | |
).launch() | |