feat(app): init bear classifier app

app.py

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+from fastai.vision.all import *
+import gradio as gr
+
+
+learn = load_learner("bear-classifier.pkl")
+labels = learn.dls.vocab
+
+def predict(img):
+    """
+    Prediction APIs.
+    """
+    _, _, probs = learn.predict(PILImage.create(img))
+
+    return {labels[i]: float(probs[i]) for i in range(len(labels))}
+
+
+demo = gr.Interface(
+    fn=predict, 
+    inputs=gr.Image(), 
+    outputs=gr.Label(num_top_classes=3), 
+    title="Bear Classifier", 
+    description="A bear classifier fine tuned on ResNet18 with a few bear samples from the internet. Its task is to recognize whether an image is a grizzy bear, a black bear or just a cute litte teddy bear!", 
+    examples=["grizzly.jpg"]
+)
+demo.launch()

bear-classifier.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:0e40bf0a5f9539cc8ad4e946e9678a919021c56a50624d1c429dd714941eb53f
+size 46976562