Add all files

app.py

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+from fastai.vision.all import *
+import gradio as gr
+
+learn = load_learner('export.pkl')
+
+labels = learn.dls.vocab
+def predict(img_fnm):
+    img = PILImage.create(img_fnm)
+    pred, pred_idx, probs = learn.predict(img)
+    return {label: float(prob) for label, prob in zip(labels, probs)}
+
+title = "Moody-nana Classifier"
+description = "Classifies an image as either happy, angry, or banana."
+examples = ["angry-banana.jpg"]
+interpretation = "default"
+enable_queue = True
+
+intf = gr.Interface(
+    fn=predict,
+    inputs=gr.inputs.Image(shape=(512, 512)),
+    outputs=gr.outputs.Label(num_top_classes=3),
+    title=title,
+    description=description,
+    examples=examples,
+    interpretation=interpretation,
+    enable_queue=enable_queue
+)
+
+intf.launch()

requirements.txt

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+fastai
+scikit-image