Create app.py

app.py

@@ -0,0 +1,15 @@
+import requests
+import gradio as gr
+from Ipython.display import Image
+from Ipython.core.display import HTML
+import skimage
+from PIL import Image as PILImage
+
+learn = load_learner("export.pkl")
+
+labels = learner.dls.vocab
+def predict(img):
+    img = PILImage.create(img)
+    return {labels[i]: float(probs[i]) for i in range(len(labels))}
+
+gr.Interface(fn=predict, inputs=inpts.Image(shape=(512, 512)), outputs=gr.outputs.Label(num_top_classes=3)).launch(share=True)