first commit, lfs, with .pkl and all the rest

app.py

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+import gradio as gr
+from fastai.vision.all import *
+import skimage
+
+learn = load_learner('export_main_char.pkl')
+
+labels = ['Lloyd Garmadon',
+          'Kai',
+          'Cole',
+          'Jay',
+          'Zane',
+          'Nya',
+          'P.I.X.A.L.',
+          'Master Wu',
+          'Lord Garmadon']
+labels.sort()
+
+
+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 = "Ninjago Main Character Classifier"
+description = "Guesses the name of the Ninjago characters. Created from the fastai demo for Gradio and HuggingFace Spaces."
+#article = "<p style='text-align: center'><a href='https://tmabraham.github.io/blog/gradio_hf_spaces_tutorial' target='_blank'>Blog post</a></p>"
+examples = ['Lloyd.jpg', 'Cole.png']
+interpretation = 'default'
+enable_queue = True
+
+gr.Interface(fn=predict, inputs=gr.inputs.Image(shape=(192, 192)), outputs=gr.outputs.Label(num_top_classes=3), title=title,
+             description=description, examples=examples, interpretation=interpretation, enable_queue=enable_queue).launch()

export_main_char.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:6c25bb7fde4f03156c577dd9fe5f3a094ca00c97faff2a7e251b4e97533412e3
+size 87482603

requirements.txt

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+fastai
+scikit-image