let's deploy to huggingface spaces

.ipynb_checkpoints/README-checkpoint.md

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+---
+title: Pizza Toppings Classifier
+emoji: 🐨
+colorFrom: gray
+colorTo: green
+sdk: gradio
+sdk_version: 3.12.0
+app_file: app.py
+pinned: false
+license: apache-2.0
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

.ipynb_checkpoints/app-checkpoint.py

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+from fastai.vision.all import *
+
+import gradio as gr
+
+def get_label(img_path):
+    one_hot = df.query('image_name == @img_path.name').iloc[:, 1:].values[0]
+    return one_hot
+
+learn = load_learner('model.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 = "Pizza Toppings Classifier"
+description = "A pizza toppings classifier trained on the MIT pizza dataset with fastai. Created as a demo for Gradio and HuggingFace Spaces."
+examples = ['onions_and_peppers.jpg', 'pepperoni_and_mushrooms.jpg']
+interpretation='default'
+enable_queue=True
+
+gr.Interface(fn=predict, inputs=gr.inputs.Image(shape=(512, 512)), outputs=gr.outputs.Label(num_top_classes=10)).launch(share=True)

app.py

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+from fastai.vision.all import *
+
+import gradio as gr
+
+def get_label(img_path):
+    one_hot = df.query('image_name == @img_path.name').iloc[:, 1:].values[0]
+    return one_hot
+
+learn = load_learner('model.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 = "Pizza Toppings Classifier"
+description = "A pizza toppings classifier trained on the MIT pizza dataset with fastai. Created as a demo for Gradio and HuggingFace Spaces."
+examples = ['onions_and_peppers.jpg', 'pepperoni_and_mushrooms.jpg']
+interpretation='default'
+enable_queue=True
+
+gr.Interface(fn=predict, inputs=gr.inputs.Image(shape=(512, 512)), outputs=gr.outputs.Label(num_top_classes=10)).launch(share=True)

model.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:a6523948621fe6636566116b10340fba01e39aa364fa7043691a21983093507c
+size 114761001

requirements.txt

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+fastai
+scikit-image