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 = 'NYC Iconic Buildings Classifier'
+description = 'This is a classifier based on fastai course, lesson 2.'
+examples = []
+interpretation = 'default'
+enable_queue = True 
+
+gr.Interface(fn=predict, inputs=gr.inputs.Image(shape=(512, 512)),
+             outputs=gr.outputs.Label(num_top_classes=3), title=title,
+             description=description, examples=examples,
+             interpretation=interpretation, enable_queue=enable_queue).launch()