app and imgs

app.py

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+
+from fastai.vision.all import *
+import skimage
+import gradio as gr
+
+learn = load_learner("god-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 = "God Classifier"
+description = "A Norse/Hindu God Classifier (fastai course exercise)"
+
+gr.Interface(fn=predict,
+             inputs=gr.inputs.Image(shape=(512, 512)),
+             outputs=gr.outputs.Label(num_top_classes=2),
+             title=title,
+             description=description,
+             examples=['hindu.jpg','norse.jpg'],
+             interpretation='default',
+             enable_queue=True).launch(share=True)

requirements.txt

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+fastai
+scikit-image