chore(typos): fixing typos

src/lerobot/datasets/compute_stats.py

@@ -550,8 +550,10 @@ def _validate_stat_value(value: np.ndarray, key: str, feature_key: str) -> None:
     if key == "count" and value.shape != (1,):
         raise ValueError(f"Shape of 'count' must be (1), but is {value.shape} instead.")
 
-    if "image" in feature_key and key != "count" and value.shape != (3, 1, 1):
-        raise ValueError(f"Shape of quantile '{key}' must be (3,1,1), but is {value.shape} instead.")
+    if "image" in feature_key and key != "count" and value.shape not in ((3, 1, 1), (1, 1, 1)):
+        raise ValueError(
+            f"Shape of quantile '{key}' must be (3,1,1) or (1,1,1) but is {value.shape} instead."
+        )
 
 
 def _assert_type_and_shape(stats_list: list[dict[str, dict]]):

src/lerobot/datasets/dataset_metadata.py

@@ -557,7 +557,7 @@ class LeRobotDatasetMetadata:
     def update_video_info(
         self,
         video_key: str | None = None,
-        camera_encoder: VideoEncoderConfig | None = None,
+        video_encoder: VideoEncoderConfig | None = None,
     ) -> None:
         """Populate per-feature video info in ``info.json``.
 
@@ -579,7 +579,7 @@ class LeRobotDatasetMetadata:
         for key in video_keys:
             if not self.features[key].get("info", None):
                 video_path = self.root / self.video_path.format(video_key=key, chunk_index=0, file_index=0)
-                self.info.features[key]["info"] = get_video_info(video_path, camera_encoder=camera_encoder)
+                self.info.features[key]["info"] = get_video_info(video_path, video_encoder=video_encoder)
 
     def update_chunk_settings(
         self,

src/lerobot/datasets/feature_utils.py

@@ -333,9 +333,7 @@ def validate_feature_image_or_video(
         actual_shape = value.shape
         c, h, w = expected_shape
         if len(actual_shape) != 3 or (actual_shape != (c, h, w) and actual_shape != (h, w, c)):
-                error_message += f"The feature '{name}' of shape '{actual_shape}' does not have the expected shape '{(c, h, w)}' or '{(h, w, c)}'.\n"
-        else:
-            error_message += f"The feature '{name}' has an unsupported expected_shape '{expected_shape}'.\n"
+            error_message += f"The feature '{name}' of shape '{actual_shape}' does not have the expected shape '{(c, h, w)}' or '{(h, w, c)}'.\n"
     elif isinstance(value, PILImage.Image):
         pass
     else:

src/lerobot/datasets/video_utils.py

@@ -372,7 +372,8 @@ def encode_video_frames(
     video_path.parent.mkdir(parents=True, exist_ok=True)
 
     # Get input frames
-    template = "frame-" + ("[0-9]" * 6) + ".png"
+    suffix = ".png" if not isinstance(video_encoder, DepthEncoderConfig) else ".tiff"
+    template = "frame-" + ("[0-9]" * 6) + suffix
     input_list = sorted(
         glob.glob(str(imgs_dir / template)), key=lambda x: int(x.split("-")[-1].split(".")[0])
     )
@@ -696,20 +697,23 @@ class StreamingVideoEncoder:
         self._episode_active = False
         self._closed = False
 
-    def start_episode(self, video_keys: list[str], depth_video_keys: list[str], temp_dir: Path) -> None:
+    def start_episode(
+        self, video_keys: list[str], temp_dir: Path, depth_video_keys: list[str] | None = []
+    ) -> None:
         """Start encoder threads for a new episode.
 
         Args:
             video_keys: List of video feature keys (e.g. ["observation.images.laptop"])
-            depth_video_keys: List of video feature keys that carry depth maps (e.g. ["observation.images.laptop_depth"])
             temp_dir: Base directory for temporary MP4 files
+            depth_video_keys: List of video feature keys that carry depth maps (e.g.
+                ["observation.images.laptop_depth"]).  Defaults to ``[]`` (no depth keys).
         """
         if self._episode_active:
             self.cancel_episode()
 
         self._dropped_frames.clear()
 
-        for video_key in video_keys + depth_video_keys:
+        for video_key in video_keys:
             frame_queue: queue.Queue = queue.Queue(maxsize=self.queue_maxsize)
             result_queue: queue.Queue = queue.Queue(maxsize=1)
             stop_event = threading.Event()
@@ -978,7 +982,8 @@ def get_video_info(
             if field_name == "vcodec":
                 continue
             video_info.setdefault(f"video.{field_name}", field_value)
-        video_info["is_depth_map"] = isinstance(video_encoder, DepthEncoderConfig)
+
+    video_info["is_depth_map"] = isinstance(video_encoder, DepthEncoderConfig)
 
     return video_info
 

src/lerobot/utils/visualization_utils.py

@@ -111,11 +111,11 @@ def log_rerun_data(
                         img_entity = (
                             rr.DepthImage(arr, colormap=rr.components.Colormap.Viridis).compress()
                             if compress_images
-                            else rr.rr.DepthImage(arr, colormap=rr.components.Colormap.Viridis)
+                            else rr.DepthImage(arr, colormap=rr.components.Colormap.Viridis)
                         )
                     else:
                         img_entity = rr.Image(arr).compress() if compress_images else rr.Image(arr)
-                    rr.log(key, entity=img_entity, static=True)
+                    rr.log(key, entity=img_entity)
 
     if action:
         for k, v in action.items():