Update app.py

app.py

@@ -4,15 +4,8 @@ from torchvision import transforms
 import gradio as gr
 import os
 
-torch.hub.download_url_to_file("https://github.com/pytorch/hub/raw/master/images/dog.jpg", "dog.jpg")
-
- # To export
-model = torch.hub.load('pytorch/vision:v0.10.0', 'shufflenet_v2_x1_0', pretrained=True).eval()
-traced_graph = torch.jit.trace(model, torch.randn(1, 3, H, W))
-traced_graph.save('shufflenet.pth')
-
- # To load
-model = torch.jit.load('shufflenet.pth').eval().to(device)
+model = torch.hub.load('pytorch/vision:v0.9.0', 'shufflenet_v2_x1_0', pretrained=True)
+model.eval()
 
 
 os.system("wget https://raw.githubusercontent.com/pytorch/hub/master/imagenet_classes.txt")
@@ -55,6 +48,6 @@ description = "                               Thesis Title: The Development of a
 article = "<p style='text-align: center'><a href='https://arxiv.org/abs/1807.11164'>Shufflenet_v2 By Bekalu Nigus Dawit</a></p>"
 
 examples = [
-            ['dog.jpg'],['pizza.jpeg'],['mushroom.jpeg'],['download.jpeg'],['ear.jpeg']
+            ['pizza.jpeg'],['mushroom.jpeg'],['download.jpeg'],['ear.jpeg']
 ]
 gr.Interface(inference, inputs, outputs, title=title, description=description, article=article, examples=examples, analytics_enabled=False).launch()