app init

app.py

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+import platform
+from fastai.vision.all import *
+import gradio as gr
+
+
+if platform.system() == 'Windows':
+    import pathlib
+    pathlib.PosixPath = pathlib.WindowsPath
+
+learn = load_learner('model.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))}
+
+title = "Painting Classifier"
+description = "A painting classifier trained to classify Picasso and Monet paintings using dataset scrapped from Duck Duck Go Image search."
+demo = gr.Interface(fn=predict,
+                    inputs=gr.Image(height=400),
+                    outputs="label",
+                    examples=["picas.jpg", "mon2.jpg"],
+                    title=title,
+                    description=description,)
+demo.launch()

model.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:5386adabdc43d11a0b01f2b5590aad867acf18dd71b179d835b4c3edd0a071b9
+size 46959550