Create rps.py

rps.py

@@ -0,0 +1,21 @@
+from fastai.vision.all import *
+import gradio as gr
+
+__all__ = ['is_rock', 'learn', 'classify_image', 'categories', 'image', 'label', 'examples', 'intf'] 
+
+def is_rock(x): return x[0].issuper() 
+
+learn = load_learner('rps_model.pkl')
+
+categories = ('paper', 'rock', 'scissors')
+
+def classify_image(img):
+    pred, idx, probs = learn.predict(img)
+    return dict(zip(categories, map(float, probs)))
+
+image = gr.inputs.Image(shape=(192,192))
+label = gr.outputs.Label()
+examples = ['rock.jpg', 'paper.jpg', 'scissors.jpg']
+
+intf = gr.Interface(fn = classify_image, inputs = image, outputs = label, examples = examples)
+intf.launch(inline=False)