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app.py

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+from fastai.vision.all import *
+import gradio as gr
+
+learn = load_learner('model.pkl')
+
+image = gr.inputs.Image(shape=(128, 128))
+label = gr.outputs.Label()
+examples = ['coral.jpg', 'crabs.jpg', 'dolphin.jpg', 'sea_rays.jpg', 'seahorse.jpg', 'turtle_tortoise.jpg']
+
+categories = ('corals','crabs','dolphin','eel','jelly fish','lobster','nudibranchs','octopus','penguin','puffers','sea rays','sea urchins','seahorse','seal','sharks','squid','starfish','turtle_tortoise','whale')
+
+def classify_img(img):
+    pred,idx,probs = learn.predict(img)
+    return dict(zip(categories, map(float, probs)))
+
+interface = gr.Interface(fn=classify_img,
+                inputs=image,
+                outputs=label,
+                examples=examples)
+
+interface.launch(inline=False)
+
+