Initial commit.

app.py

@@ -171,8 +171,8 @@ def predict(input_img):
     return drawing_blend_pseudo, drawing_blend_cs
 
 
-title = '<h1 align="center">Drive&Segment</h1>'
-description = 'Gradio Demo accompanying paper "Drive&Segment: Unsupervised Semantic Segmentation of Urban Scenes via Cross-modal Distillation"\nBecause of the CPU-only inference, it might take up to 20s for large images.\nRight now, it uses the Segmenter model trained on nuScenes and with a simplified inference scheme (for the sake of speed).'
+title = 'Drive&Segment'
+description = 'Gradio Demo accompanying paper "Drive&Segment: Unsupervised Semantic Segmentation of Urban Scenes via Cross-modal Distillation"\nBecause of the CPU-only inference, it might take up to 20s for large images.\nRight now, it uses the Segmenter model trained on nuScenes and with a simplified inference scheme (for the sake of speed). Please see description below the app for more details.'
 # article = "<p style='text-align: center'><a href='https://vobecant.github.io/DriveAndSegment/' target='_blank'>Project Page</a> | <a href='https://github.com/vobecant/DriveAndSegment' target='_blank'>Github</a></p>"
 article = """
 <h1 align="center">🚙📷 Drive&Segment: Unsupervised Semantic Segmentation of Urban Scenes via Cross-modal Distillation</h1>