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import gradio as gr | |
from huggingface_hub import from_pretrained_keras | |
def infer(filepath): | |
image_tensor = np.load(filepath) | |
prediction = model.predict(np.expand_dims(image_tensor, axis=0))[0] | |
confidence = 100 * (1 - prediction[0]) | |
return confidence | |
model = from_pretrained_keras('jalFaizy/3D_CNN') | |
filepath = gr.inputs.File() | |
text = gr.outputs.Textbox() | |
iface = gr.Interface( | |
infer, | |
filepath, | |
text, | |
title='3D CNN for CT scans', | |
examples=['example_1_normal.npy'] | |
) | |
iface.launch() |