Pushing app file, examples & requirements

app.py

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+from fastai.vision.all import *
+import gradio as gr
+import skimage
+
+learn = load_learner('puppy.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))}
+
+title = "Puppy Breed Classifier"
+description = "A puppy breed classifier trained on a custom dataset from DDG images with fastai. Created as a demo for Gradio and HuggingFace Spaces."
+image = gr.Image(height=215, width=215)
+label = gr.Label()
+examples = [['corgi puppy.jfif'], ['golden retriever.jfif'], ['husky bear.jfif']]
+
+
+intf = gr.Interface(fn=predict, inputs=image, outputs=label, title=title, description=description,examples=examples)
+intf.launch(inline=False)

puppy.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:ef4d12e3ff314d1f0840b46e30673f620e2b466fac88ddde28269031d2dd9bb4
+size 46973950

requirements.txt

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+fastai
+scikit-image