Create app.py

app.py

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+import gradio as gr
+from fastai.vision.all import *
+import skimage
+
+learn = load_learner('export.pkl')
+
+labels = learn.dls.vocab
+def predict(img):
+    img = PILImage.create(img)
+    pred,pred_idx,probs = learn.predict(img)
+    prediction = str(pred)
+    
+    return prediction
+
+
+title = "Lung cancer detection with Deep Transfer Learning(ResNet18)"
+description = "<p style='text-align: center'><b>As a radiologist or oncologist, it is crucial to know what is wrong with a lung CT image.<b><br><b>Upload the breast X-ray image to know what is wrong with a patients breast with or without inplant<b><p>"
+article="<p style='text-align: center'>Web app is built and managed by Mr.<b></p>"
+examples = ['img1.jpeg', 'img2.jpeg']
+enable_queue=True
+#interpretation='default'
+
+gr.Interface(fn=predict,inputs=gr.inputs.Image(shape=(512, 512)),outputs=gr.outputs.Label(num_top_classes=3),title=title,description=description,article=article,examples=examples,enable_queue=enable_queue).launch()