Update gradio_app.py

gradio_app.py

@@ -31,7 +31,7 @@ description = """
   </p>
   <h2 align="center">
     <p>ECCV 2024</p>
-    <a href="" align="center">Paper</a> | <!--TODO: update link-->
+    <a href="https://arxiv.org/pdf/2409.06704" align="center">Paper</a> |
     <a href="https://github.com/cvg/GeoCalib" align="center">Code</a> |
     <a href="https://colab.research.google.com/drive/1oMzgPGppAPAIQxe-s7SRd_q8r7dVfnqo#scrollTo=etdzQZQzoo-K" align="center">Colab</a>
   </h2>
@@ -80,8 +80,8 @@ def inference(img, camera_model):
     save_keys = ["camera", "gravity"] + [f"{k}_uncertainty" for k in ["roll", "pitch", "vfov", "focal"]]
     res = {k: v.cpu() for k, v in out.items() if k in save_keys}
     # not converting to numpy results in gpu abort
-    res["up_confidence"] = torch.tensor(out["up_confidence"].cpu().numpy())
-    res["latitude_confidence"] = torch.tensor(out["latitude_confidence"].cpu().numpy())
+    res["up_confidence"] = out["up_confidence"].cpu().numpy()
+    res["latitude_confidence"] = out["latitude_confidence"].cpu().numpy()
     return res
 
 
@@ -155,10 +155,10 @@ def update_plot(
         viz2d.plot_latitudes([lat[0, 0]], axes=[ax[0]])
 
     if plot_up_confidence:
-        viz2d.plot_confidences([inference_result["up_confidence"][0]], axes=[ax[0]])
+        viz2d.plot_confidences([torch.tensor(inference_result["up_confidence"][0])], axes=[ax[0]])
 
     if plot_latitude_confidence:
-        viz2d.plot_confidences([inference_result["latitude_confidence"][0]], axes=[ax[0]])
+        viz2d.plot_confidences([torch.tensor(inference_result["latitude_confidence"][0])], axes=[ax[0]])
 
     fig.canvas.draw()
     img = np.array(fig.canvas.renderer.buffer_rgba())