Create app.py

app.py

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+import gradio as gr
+from fastai.vision.all import *
+import skimage
+
+learn = load_learner('model.pkl')
+#examples = [['Images/PKG - Breast-Metastases-MSKCC/Breast-Metastases-MSKCC/HobI16-053768896760.jpeg'], ['Images/PKG - CPTAC-BRCA/BRCA/01BR001-4ffefc66-d0ba-4a36-b4fa-35bd91.jpeg']]
+labels = learn.dls.vocab
+
+def predict(img):
+    img = PILImage.create(img)
+    pred,pred_idx,probs = learn.predict(img)
+    return {labels[i]: float(probs[i]) for i in range(len(labels))}
+
+title = "Proliferative Retinopathy Detection"
+description = """Detects severity of diabetic retinopathy - 
+
+    0 - No DR
+
+    1 - Mild
+
+    2 - Moderate
+
+    3 - Severe
+
+    4 - Proliferative DR
+"""
+article="<p style='text-align: center'><a href='https://www.kaggle.com/code/josemauriciodelgado/proliferative-retinopathy' target='_blank'>Notebook</a></p>"
+interpretation='default'
+enable_queue=True
+
+gr.Interface(fn=predict,inputs=gr.inputs.Image(shape=(512, 512)),outputs=gr.outputs.Label(num_top_classes=6),title=title,description=description,article=article,examples=examples , interpretation=interpretation,enable_queue=enable_queue).launch()