clean title

app.py

@@ -21,29 +21,12 @@ from perspective2d.utils import draw_from_r_p_f_cx_cy
 
 
 
-title = "Perspective Fields Demo"
-
-description = """
-<p style="text-align: center">
-    <a href="https://jinlinyi.github.io/PerspectiveFields/" target="_blank">Project Page</a> | 
-    <a href="https://arxiv.org/abs/2212.03239" target="_blank">Paper</a> | 
-    <a href="https://github.com/jinlinyi/PerspectiveFields" target="_blank">Code</a> | 
-    <a href="https://www.youtube.com/watch?v=sN5B_ZvMva8&themeRefresh=1" target="_blank">Video</a>
-</p>
-<h2>Gradio Demo</h2>
-<p>Try our Gradio demo for Perspective Fields for single image camera calibration. You can click on one of the provided examples or upload your own image.</p>
-<h3>Available Models:</h3>
-<ol>
-    <li><strong>PersNet-360Cities:</strong> PerspectiveNet trained on the 360Cities dataset. This model predicts perspective fields and is designed to be robust and generalize well to both indoor and outdoor images.</li>
-    <li><strong>PersNet_Paramnet-GSV-uncentered:</strong> A combination of PerspectiveNet and ParamNet trained on the Google Street View (GSV) dataset. This model predicts camera Roll, Pitch, and Field of View (FoV), as well as the Principal Point location.</li>
-    <li><strong>PersNet_Paramnet-GSV-centered:</strong> PerspectiveNet+ParamNet trained on the GSV dataset. This model assumes the principal point is at the center of the image and predicts camera Roll, Pitch, and FoV.</li>
-</ol>
-"""
-
-
-article = """
-<p style='text-align: center'><a href='https://arxiv.org/abs/2212.03239' target='_blank'>Perspective Fields for Single Image Camera Calibrations</a> | <a href='https://github.com/jinlinyi/PerspectiveFields' target='_blank'>Github Repo</a></p>
-"""
+title = ""
+
+description = ""
+
+
+article = ""