fix(non_annotated_t4_to_deepen): fix frame skipping logic (#153)

* fix skip frame logic Signed-off-by: Shunsuke Miura <shunsuke.miura@tier4.jp> * increment the version number Signed-off-by: Shunsuke Miura <shunsuke.miura@tier4.jp> * refactor: extract get_camera_token into a separate function Signed-off-by: Shunsuke Miura <shunsuke.miura@tier4.jp> --------- Signed-off-by: Shunsuke Miura <shunsuke.miura@tier4.jp>
tier4 · Sep 19, 2024 · 4853518 · 4853518
1 parent 76286a6
commit 4853518
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diff --git a/perception_dataset/deepen/non_annotated_t4_to_deepen_converter.py b/perception_dataset/deepen/non_annotated_t4_to_deepen_converter.py
@@ -99,19 +99,7 @@ def _convert_one_frame(self, input_dir: str, output_dir: str, frame_index: int):
 
         for camera_sensor_type in self._camera_sensor_types:
             camera_channel = camera_sensor_type.value["channel"]
-
-            if camera_channel in sample["data"].keys():
-                camera_token = sample["data"][camera_channel]
-            else:
-                sample_data = [s for s in nusc.sample_data if s["sample_token"] == sample["token"]]
-                for sensor in sample_data:
-                    if sensor["channel"] == camera_channel:
-                        camera_token = sensor["token"]
-                        break
-                logger.warning(
-                    f"camera: {camera_channel} not found in frame {frame_index}, skipping this frame..."
-                )
-                return
+            camera_token: str | None = self._get_camera_token(camera_channel, sample, nusc)
 
             camera_path, _, cam_intrinsic = nusc.get_sample_data(camera_token)
             data_dict: Dict[str, Any] = self._get_data(nusc, camera_token)
@@ -139,6 +127,28 @@ def _convert_one_frame(self, input_dir: str, output_dir: str, frame_index: int):
 
         config_data.save_json(output_dir)
 
+    @staticmethod
+    def _get_camera_token(camera_channel: str, sample, nusc) -> str | None:
+        """Get camera token for `camera_channel` in the given `sample` data from a NuScenes dataset.
+        Args:
+            camera_channel (str): Camera channel name e.g. CAM_FRONT to look for
+            sample: Sample data for a specific frame from NuScenes = `nusc.sample[frame_index]`
+            nusc (NuScenes): NuScenes dataset
+        Return:
+            camera_token: str | None
+                None if not found
+        """
+        camera_token: str | None = None
+        if camera_channel in sample["data"].keys():
+            camera_token = sample["data"][camera_channel]
+        else:
+            sample_data = [s for s in nusc.sample_data if s["sample_token"] == sample["token"]]
+            for sensor in sample_data:
+                if sensor["channel"] == camera_channel:
+                    camera_token = sensor["token"]
+                    break
+        return camera_token
+
     def _get_data(self, nusc: NuScenes, sensor_channel_token: str) -> Dict[str, Any]:
         sd_record = nusc.get("sample_data", sensor_channel_token)
         cs_record = nusc.get("calibrated_sensor", sd_record["calibrated_sensor_token"])

diff --git a/pyproject.toml b/pyproject.toml
@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "perception-dataset"
-version = "1.0.14"
+version = "1.0.15"
 description = "TIER IV Perception dataset has modules to convert dataset from rosbag to t4_dataset"
 authors = [
     "Yusuke Muramatsu <yusuke.muramatsu@tier4.jp>",