Upload app.py

app.py

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+import gradio as gr
+from fastai.vision.all import *
+import skimage
+
+learn = load_learner('export.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 = 'Bear Classifier'
+description = 'A bear classifier trained on random images from internet with fastai. Created as a demo for Gradio and HuggingFace Spaces.'
+examples = ['GrizzlyBearJeanBeaufort.jpg']
+
+gr.Interface(fn = predict,
+inputs = 'image',
+outputs = 'label',
+title = title,
+description = description,
+examples = examples).launch()