full update

app.py

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+from fastai.vision.all import *
+import gradio as gr
+import skimage
+
+learn = load_learner('pet_class_model_resnet18.pkl')
+
+examples = ['dog.jpg', 'cat.jpg', 'dunno.jpg']
+
+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))}
+
+gr.Interface(fn=predict, 
+             inputs=gr.inputs.Image(shape=(512, 512)), 
+             outputs=gr.outputs.Label(num_top_classes=3),
+             examples=examples,
+             title="Pet Breed Classifier",
+             interpretation='default',
+             enable_queue=True
+             ).launch(share=True)

pet_class_model_resnet18.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:ff30ff6ebf0d0985c57b7dc59c497208ea3565cbe16ee932c53bc410698ac3ce
+size 47135119

requirements.txt

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+fastai
+scikit-image