Create app.py

app.py

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+import gradio as gr
+from fastai.vision.all import *
+
+learn_inf = load_learner('model.pkl')
+categories = learn_inf.dls.vocab
+
+def classify_image(img):
+    pred,pred_idx,probs = learn_inf.predict(img)
+    return dict(zip(categories, map(float, probs))) 
+
+iface = gr.Interface(
+    title = "Is it Huggable?",
+    description = "An image classifier that tells if something's huggable or not?",
+    article = "<p style='text-align: center'><a href='https://github.com/daspartho/is-it-huggable' target='_blank'>Github</a></p>",
+    fn=classify_image, 
+    inputs=gr.Image(shape=(224,224)), 
+    outputs=gr.outputs.Label(),
+    #examples=['examples/dog.jpg', 'examples/cactus.jpg', 'examples/plushie.jpg', 'examples/snowman.jpg', 'examples/chainsaw.jpg', 'examples/shark.jpg','examples/bunny.jpg', 'examples/knife.jpg', 'examples/tiger.jpg', 'examples/trex.jpg'],
+    live=True,
+    enable_queue=True
+    )
+iface.launch()