fix to small tracks

src/ml_tools/datasetstructures.py

@@ -1095,11 +1095,16 @@ def get_segments(
 
             for i in range(segment_count):
                 if random_mask:
-                    mask_start = i * 25
-                    frame_indices = list(whole_indices[0:mask_start].copy())
-                    frame_indices.extend(whole_indices[mask_start + 25 :].copy())
-                    frame_indices = [f for f in frame_indices if f not in used_indices]
-                    frame_indices = np.uint32(frame_indices)
+                    if len(whole_indices) < 40:
+                        frame_indices = whole_indices.copy()
+                    else:
+                        mask_start = i * 25
+                        frame_indices = list(whole_indices[0:mask_start].copy())
+                        frame_indices.extend(whole_indices[mask_start + 25 :].copy())
+                        frame_indices = [
+                            f for f in frame_indices if f not in used_indices
+                        ]
+                        frame_indices = np.uint32(frame_indices)
                     np.random.shuffle(frame_indices)
 
                 # always get atleast one segment, not doing annymore

src/ml_tools/interpreter.py

@@ -126,6 +126,7 @@ def preprocess(self, clip, track, **args):
                 predict_from_last,
                 segment_frames=segment_frames,
                 dont_filter=args.get("dont_filter", False),
+                min_segments=args.get("min_segments"),
             )
         else:
             frames, preprocessed, masses = self.preprocess_frames(
@@ -290,6 +291,7 @@ def preprocess_segments(
         predict_from_last=None,
         segment_frames=None,
         dont_filter=False,
+        min_segments=None,
     ):
         from ml_tools.preprocess import preprocess_frame, preprocess_movement
 
@@ -304,7 +306,7 @@ def preprocess_segments(
             max_segments=max_segments,
             dont_filter=dont_filter,
             filter_by_fp=False,
-            min_segments=1,
+            min_segments=min_segments,
         )
         frame_indices = set()
         for segment in segments:

src/modelevaluate.py

@@ -381,9 +381,8 @@ def load_clip_data(cptv_file):
     for track in clip.tracks:
         try:
             frames, preprocessed, masses = worker_model.preprocess(
-                clip_db, track, frames_per_classify=25, dont_filter=True
+                clip_db, track, frames_per_classify=25, dont_filter=True, min_segments=1
             )
-
             data.append(
                 (
                     f"{track.clip_id}-{track.get_id()}",