Upload app.py

app.py

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+import gradio as gr
+from fastai.vision.all import *
+import skimage
+
+learn = load_learner('movements_05_02_22_4pm.pkl')
+
+def predict(img):
+    labels = learn.dls.vocab
+    im = PILImage.create(img)
+    pred,pred_idx,probs = learn.predict(im)
+    return {label: float(prob) for (label,prob) in zip(labels,probs)}
+
+examples = [f"Image{n:02d}" for n in range(25)]
+
+gr.Interface(fn=predict,
+             inputs=gr.inputs.Image(shape=((512,512))),
+             outputs=gr.outputs.Label(num_top_classes=5),
+             title = "Art Movements",
+             examples =  examples
+             description= "What Art Movement Matches the Image Best? Expressionism | Impressionism | Hudson River School | Ukiyo-e | Pre-Raphaelite").launch(share=True, enable_queue=True)