Update app.py

app.py

@@ -99,7 +99,7 @@ def predict(input_img, ver):
 
     drawing = 0
     with torch.no_grad():
-        if ver == 'style 2':
+        if ver == 'Simple Lines':
             drawing = model2(input_img)[0].detach()
         else:
             drawing = model1(input_img)[0].detach()
@@ -108,13 +108,18 @@ def predict(input_img, ver):
     return drawing
 
 title="informative-drawings"
-description="Gradio Demo for line drawing generation. "
-# article = "<p style='text-align: center'><a href='TODO' target='_blank'>Project Page</a> | <a href='codelink' target='_blank'>Github</a></p>"
-examples=[['cat.png', 'style 1'], ['bridge.png', 'style 1'], ['lizard.png', 'style 2'],]
+description="Image to Line Drawing"
+# article = "<p style='text-align: center'></p>"
+examples=[
+['01.png', 'Simple Lines'], ['02.png', 'Simple Lines'], ['03.png', 'Simple Lines'],
+['04.png', 'Simple Lines'], ['05.png', 'Simple Lines'], ['06.png', 'Simple Lines'],
+['01.png', 'Complex Lines'], ['02.png', 'Complex Lines'], ['03.png', 'Complex Lines'],
+['04.png', 'Complex Lines'], ['05.png', 'Complex Lines'], ['06.png', 'Complex Lines']
+]
 
 
 iface = gr.Interface(predict, [gr.inputs.Image(type='filepath'),
-    gr.inputs.Radio(['style 1','style 2'], type="value", default='style 1', label='version')],
+    gr.inputs.Radio(['Complex Lines','Simple Lines'], type="value", default='Simple Lines', label='version')],
     gr.outputs.Image(type="pil"), title=title,description=description,examples=examples)
 
 iface.launch()