[VideoToFrames] pass annotations too

bob/pad/face/transformer/VideoToFrames.py

 from sklearn.base import TransformerMixin, BaseEstimator
 import bob.pipelines as mario
+from bob.pipelines.wrappers import _frmt
 import logging
 
 logger = logging.getLogger(__name__)
 
 
 class VideoToFrames(TransformerMixin, BaseEstimator):
-    """Expands frame containers to frame-based samples only when transform is called.
-    When fit_transform is called, it just converts frame containers to numpy arrays.
+    """Expands video samples to frame-based samples only when transform is called.
     """
 
     def transform(self, video_samples):
-        logger.info(
-            f"Calling {self.__class__.__name__}.transform from VideoToFrames"
-        )
+        logger.debug(f"{_frmt(self)}.transform")
         output = []
         for sample in video_samples:
-            for frame, frame_id in zip(sample.data, sample.data.indices):
-                new_sample = mario.Sample(frame, frame_id=frame_id, parent=sample)
+            annotations = getattr(sample, "annotations", {})
+
+            for frame, frame_id in zip(sample.data.data, sample.data.indices):
+                new_sample = mario.Sample(
+                    frame,
+                    frame_id=frame_id,
+                    annotations=annotations.get(str(frame_id)),
+                    parent=sample,
+                )
                 output.append(new_sample)
+
         return output
 
     def fit(self, X, y=None, **fit_params):