slop

server/src/services/roverLearningService/workers/observations.py

@@ -0,0 +1,45 @@
+"""Shared causal 10 Hz sampling for recorded and live video."""
+import math
+
+
+def decision_frames(frames):
+    """Yield decision time, latest past image, and its actual capture timestamp.
+
+    Sampling every third/fourth decoded frame leaves holes at rates such as 25
+    FPS. A fixed grid covers each 100ms command interval exactly once. A frame
+    after the decision can release the pending tick, but is never its input.
+    """
+    previous = None
+    previous_time = None
+    tick = None
+    for frame in frames:
+        if frame.pts is None:
+            raise ValueError('Video frame has no timestamp')
+        stamp = float(frame.pts * frame.time_base) * 1000
+        if not math.isfinite(stamp) or (previous_time is not None and stamp < previous_time):
+            raise ValueError('Invalid/nonmonotonic video timestamps')
+        if tick is None:
+            tick = stamp
+        while tick < stamp - .01:
+            # Do not synthesize observations over missing/stalled video. History
+            # selection will reject a temporal gap until fresh history exists.
+            if previous is not None and tick - previous_time <= 200:
+                yield tick, previous, previous_time
+            elif stamp - tick > 200:
+                tick += max(1, math.floor((stamp - tick) / 100)) * 100
+                continue
+            tick += 100
+        if abs(stamp - tick) <= .01:
+            yield tick, frame, stamp
+            tick += 100
+        previous, previous_time = frame, stamp
+
+
+def history_frames(history, stamp):
+    selected = []
+    for offset in (900, 600, 300, 0):
+        candidates = [row for row in history if row[0] <= stamp - offset + .01]
+        if not candidates or stamp - offset - candidates[-1][0] > 200:
+            return []
+        selected.append(candidates[-1])
+    return selected