Commit initial model

app.py

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+from fastai.vision.all import *import gradio as gr
+
+
+learn = load_learner('model.pkl')
+
+
+labels = learn.dls.vocab
+def predict(img):
+    pil_img = PILImage.create(img)
+    pred, pred_idx, probs = learn.predict(pil_img)
+    result = {}
+    for label_idx, label in enumerate(labels):
+        result[label] = float(probs[label_idx])
+    return result
+
+
+gr.Interface(
+    fn=predict,
+    inputs=gr.inputs.Image(shape=(512, 512)),
+    outputs=gr.outputs.Label(num_top_classes=3),
+    examples=['border_collie.jpg'],
+).launch()

model.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:9a04c41daeb4526770f89f7df1d857892a196482d7f4ca2dde358597a9deb7f7
+size 47033105

requirements.txt

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+fastai
+scikit-image