uPDATE The code

.Rhistory

@@ -0,0 +1,4 @@
+setwd("~/GitHub/FastAI/Big_Cat_Classification")
+setwd("~/GitHub/FastAI/Big_Cat_Classification")
+reticulate::repl_python()
+reticulate::repl_python()

app.py

@@ -1,3 +1,5 @@
+__all__ = ['learn', 'classify_image', 'categories', 'image', 'label', 'examples', 'intf']
+
 import gradio as gr
 from fastai.vision.all import *
 
@@ -10,17 +12,13 @@ def classify_images(img):
   pred,idx,probs = learn.predict(img)
   return dict(zip(categories, map(float, probs)))
 
-images = gr.inputs.Image(shape = (192,192))
+image = gr.inputs.Image(shape=(192, 192))
 label = gr.outputs.Label()
-#examples = ["Cat.jpg","Fox.jpg","Dog.jpeg"]
+examples = ["Cat.jpg","Fox.jpg","Dog.jpeg"]
 
 #gr.Interface(fn=predict,inputs=gr.inputs.Image(shape=(512, 512)),outputs=gr.outputs.Label(num_top_classes=3),title=title,description=description,article=article,examples=examples,interpretation=interpretation,enable_queue=enable_queue).launch(share=True)
 
-intf = gr.Interface(
-  fn=classify_images,
-  inputs=gr.Image(shape=(192, 192)),
-  outputs=gr.Label(),
-  examples = ["Cat.jpg","Fox.jpg","Dog.jpeg"])
+intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)
 intf.launch(inline=False)