为采集帧绑定主机时间与来源信息

采集时间随图像穿过处理队列，并修正未读帧的丢帧计数。通过采集与流水线针对性测试。

tests/test_pipeline.py

@@ -8,7 +8,7 @@ import time
 import numpy as np
 import pytest
 
-from orisys import FrameSnapshot, StreamPipeline
+from orisys import FrameSnapshot, ProducedFrame, StreamPipeline
 
 
 class FakeSensor:
@@ -149,6 +149,30 @@ def test_on_frame_receives_every_frame_in_order():
     assert pipe.stats.published == 12
 
 
+def test_producer_metadata_stays_with_its_image_through_the_queues():
+    sensor = FakeSensor(flow_delay=0.002)
+    frames = []
+    produced = 0
+
+    def produce():
+        nonlocal produced
+        if produced == 12:
+            return None
+        value = produced
+        produced += 1
+        return ProducedFrame(sensor.make_frame(value), {"source_seq": value})
+
+    pipe = StreamPipeline(sensor, produce, on_frame=frames.append)
+    pipe.start()
+    deadline = time.perf_counter() + 10.0
+    while len(frames) < 12 and time.perf_counter() < deadline:
+        time.sleep(0.001)
+    pipe.stop()
+    assert len(frames) == 12
+    for snap in frames:
+        assert snap.source_metadata["source_seq"] == int(snap.image[0, 0])
+
+
 def test_forces_come_from_the_matching_frame():
     """Each snapshot must carry the forces computed from its own frame's flow."""
     sensor = FakeSensor()