Create app.py

app.py

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+import gradio as gr
+
+learn = load_learner('/kaggle/input/models/ModelSuperKek.pkl')
+
+label = ['Cancer', 'No Cancer']
+
+def classificador(im):
+    pred,idx,probs = learn.predict(im)
+    return dict(zip(label, map(float, probs)))
+
+imatge = gr.inputs.Image(shape=(192,192))
+label = gr.outputs.Label()
+example = ['/kaggle/input/rsna22-bal/rsna22_bal/rsna22_bal/images_png/12305_1995339680_L.png', '/kaggle/input/rsna22-bal/rsna22_bal/rsna22_bal/images_png/10234_173054723_L.png' ]
+
+intf = gr.Interface(fn=classificador, inputs = imatge, outputs = label)
+intf.launch(inline=False)