Accept near-complete frame extraction chunks

video_ai_analysis_poc/ffmpeg_sampler.py

@@ -126,7 +126,11 @@ def sample_video_frames(
             timeline_start_epoch=start_epoch,
             timezone_name=timezone_name,
         )
-        if records and (max_frames is None or len(records) >= max_frames):
+        if _has_usable_frames_after_nonzero_exit(
+            records,
+            max_frames=max_frames,
+            ffmpeg_config=ffmpeg_config,
+        ):
             _attach_success_evidence(
                 records,
                 command,
@@ -142,6 +146,24 @@ def sample_video_frames(
     return records
 
 
+def _has_usable_frames_after_nonzero_exit(
+    records: list[dict[str, Any]],
+    *,
+    max_frames: int | None,
+    ffmpeg_config: dict[str, Any],
+) -> bool:
+    if not records:
+        return False
+    if max_frames is None or len(records) >= max_frames:
+        return True
+    min_ratio = float(ffmpeg_config.get("min_success_frame_ratio", 0.98))
+    missing_tolerance = int(ffmpeg_config.get("max_missing_success_frames", 5))
+    return (
+        len(records) >= math.floor(max_frames * min_ratio)
+        or max_frames - len(records) <= missing_tolerance
+    )
+
+
 def _replace_video_records(
     manifest_path: Path,
     video_id: str,