app

app.py

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+import gradio as gr
+from fastai.vision.all import load_learner
+
+model = load_learner('export.pkl')
+
+categories = tuple(['eagle', 'hawk', 'falcon', 'owl', 'vulture'].sort())
+
+def classify_bird(img):
+    pred, idx, probs = model.predict(img)
+    return dict(zip(categories, map(float, probs)))
+
+image = gr.inputs.Image(shape=(256, 256))
+label = gr.outputs.Label(num_top_classes=5)
+
+examples = ['eagle.jpg', 'hawk.jpg', 'falcon.jpg', 'owl.jpg', 'vulture.jpg']
+
+iface = gr.Interface(
+    fn=classify_bird,
+    inputs=image, 
+    outputs=label, 
+    examples=examples, 
+    title='Birds of Prey Classifier', 
+    description='Classifies images as one of 5 classes: eagle, hawk, falcon, owl, vulture',
+    allow_flagging=False
+)
+iface.launch()

export.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:65ceb5097fafd37d5b07ebd3ae474b987889654cc6effbbd62af0e89fc5bf703
+size 46970347