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app.py

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+import gradio as gr
+from fastai.vision.all import *
+import skimage
+
+title = "Homer or Peter"
+examples = ["homer_1.jpg",
+            "homer_2.jpg",
+            "homer_3.jpg",
+            "peter_1.jpg",
+            "peter_2.jpg"]
+interpretation='default'
+enable_queue=True
+
+learn = load_learner('homer-or-peter.pkl')
+
+labels = learn.dls.vocab
+def predict(img):
+    img = PILImage.create(img)
+    pred, pred_idx, 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=(512, 512)),
+             outputs=gr.components.Label(num_top_classes=3),
+             title=title,
+             examples=examples,
+             interpretation=interpretation
+            ).launch(enable_queue=enable_queue)

homer-or-peter.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:3aba321e5b490604499c4f800c997b2f2bfb6fc4e8b2c656a1f21d0746acebc4
+size 46959494

requirements.txt

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+fastai
+scikit-image