Update app.py

app.py

@@ -0,0 +1,33 @@
+import os
+import gradio as gr
+from PIL import Image
+import torch
+
+os.system('mkdir weights')
+os.system('curl -L -o weights/hybridnets.pth https://github.com/datvuthanh/HybridNets/releases/download/v1.0/hybridnets.pth')
+
+def inference(img):
+    
+    img.save("demo/image/1.jpg", "JPEG")
+    os.system('python hybridnets_test.py -w weights/hybridnets.pth --source demo/image --output demo_result --imshow False --imwrite True')
+    
+    return 'demo_result/1.jpg'
+        
+title="HybridNets Demo"
+
+description="Gradio demo for HybridNets: End2End Perception Network pretrained on BDD100k Dataset. To use it, simply upload your image or click on one of the examples to load them. Read more at the links below"
+
+article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2203.09035' target='_blank'>ybridNets: End2End Perception Network</a> | <a href='https://github.com/datvuthanh/HybridNets' target='_blank'>Github Repo</a></p>"
+
+
+examples=[['1.jpg']]
+gr.Interface(
+    inference, 
+    [gr.inputs.Image(type="pil", label="Input")], 
+    gr.outputs.Image(type="file", label="Output"),
+    title=title,
+    description=description,
+    article=article,
+    enable_queue=True,
+    examples=examples
+    ).launch(debug=True)