[DRAFT] Mip-Splatting implementation

examples/datasets/colmap.py

@@ -182,6 +182,7 @@ def __init__(
         self.image_names = image_names  # List[str], (num_images,)
         self.image_paths = image_paths  # List[str], (num_images,)
         self.camtoworlds = camtoworlds  # np.ndarray, (num_images, 4, 4)
+        self.worldtocams = np.linalg.inv(camtoworlds)  # np.ndarray, (num_images, 4, 4)
         self.camera_ids = camera_ids  # List[int], (num_images,)
         self.Ks_dict = Ks_dict  # Dict of camera_id -> K
         self.params_dict = params_dict  # Dict of camera_id -> params
@@ -254,7 +255,8 @@ def __getitem__(self, item: int) -> Dict[str, Any]:
         K = self.parser.Ks_dict[camera_id].copy()  # undistorted K
         params = self.parser.params_dict[camera_id]
         camtoworlds = self.parser.camtoworlds[index]
-
+        worldtocams = self.parser.worldtocams[index]
+
         if len(params) > 0:
             # Images are distorted. Undistort them.
             mapx, mapy = (
@@ -277,6 +279,7 @@ def __getitem__(self, item: int) -> Dict[str, Any]:
         data = {
             "K": torch.from_numpy(K).float(),
             "camtoworld": torch.from_numpy(camtoworlds).float(),
+            "worldtocam": torch.from_numpy(worldtocams).float(),
             "image": torch.from_numpy(image).float(),
             "image_id": item,  # the index of the image in the dataset
         }