Create app.py

app.py

@@ -0,0 +1,12 @@
+import numpy as np
+
+def image_classifier(inp):
+  confidence_scores = np.random.rand(3)
+  confidence_scores/= np.sum(confidence_scores)
+  classes= ['cable','case', 'cpu']
+  result= {classes[i]: confidence_scores[i] for i in range(3)}
+  return result
+
+import gradio as gr
+demo = gr.Interface(fn=image_classifier, inputs = "image", outputs = "label")
+demo.launch()