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grado_test.py

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+
+from fastai.vision.all import *
+
+learn = load_learner('orange_cats.pkl')
+
+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))}
+
+import gradio as gr
+title = "Cat, croissant, leaves, or yellow tiles?"
+description = "This model can classify images into 4 categories: cat, croissant, leaves, or yellow tiles. Upload an image or click an example image to test the model."
+examples =['examples/cat.jpg', 'examples/Croissant.png', 'examples/leaves.jpg', 'examples/Tiles.jpg']
+gr.Interface(fn=predict,examples=examples, title=title,description=description,inputs=gr.Image(), outputs=gr.Label(num_top_classes=3)).launch(share=True)
+
+
+

orange_cats.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:cf1c4258a948cd56892879c90e773e8b2b10f10b50588dcf080bbb2114e781c1
+size 46981336