Fix typing of count.data and possible error due to number of centroid…

…s mismatch

pyannote/audio/pipelines/speaker_diarization.py

@@ -547,7 +547,7 @@ def apply(
         # during counting, we could possibly overcount the number of instantaneous
         # speakers due to segmentation errors, so we cap the maximum instantaneous number
         # of speakers by the `max_speakers` value
-        count.data = np.minimum(count.data, max_speakers)
+        count.data = np.minimum(count.data, max_speakers).astype(np.int8)
 
         # reconstruct discrete diarization from raw hard clusters
 
@@ -604,18 +604,21 @@ def apply(
         if not return_embeddings:
             return diarization
 
+        # The number of centroids may be smaller than the number of speakers
+        # in the annotation. This can happen if the number of active speakers
+        # obtained from `speaker_count` for some frames is larger than the number
+        # of clusters obtained from `clustering`. In this case, we append zero embeddings
+        # for extra speakers
+        if len(diarization.labels()) > centroids.shape[0]:
+            centroids = np.pad(centroids, (0, len(diarization.labels()) - centroids.shape[0]))
+
         # re-order centroids so that they match
         # the order given by diarization.labels()
         inverse_mapping = {label: index for index, label in mapping.items()}
         centroids = centroids[
             [inverse_mapping[label] for label in diarization.labels()]
         ]
 
-        # FIXME: the number of centroids may be smaller than the number of speakers
-        # in the annotation. This can happen if the number of active speakers
-        # obtained from `speaker_count` for some frames is larger than the number
-        # of clusters obtained from `clustering`. Will be fixed in the future
-
         return diarization, centroids
 
     def get_metric(self) -> GreedyDiarizationErrorRate: