initial version

app.py

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+import gradio as gr
+from fastai.vision.all import *
+
+learn = load_learner("export.pkl")
+
+labels = learn.dls.vocab
+
+
+def predict(img):
+    img = PILImage.create(img)
+    _, _, probs = learn.predict(img)
+    return {labels[i]: float(probs[i]) for i in range(len(labels))}
+
+gr.Interface(
+    fn=predict,
+    inputs=gr.components.Image(shape=(400, 400)),
+    outputs=gr.components.Label(num_top_classes=2),
+    title="Does my sighthound have a corn?",
+    description="given a picture of a paw. does it have a corn?",
+    examples=[
+        "corn_01.jpg",
+        "corn_02.jpg",
+        "corn_03.jpg",
+        "no_corn_01.jpg",
+        "no_corn_02.jpg",
+    ],
+).launch(enable_queue=True)

export.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:212dd162547e13599c42f1625c1b2b31627278cc2b8d205a403e531bd16a73a4
+size 791507375

requirements.txt

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+fastai==2.7.9