fix(ceus): 降低长视频内存峰值，快照开跑即写，build 核对 CEUS 运行与交付包

- 内存：prepare_segmentation 改为流式解码，只留分屏和配准的抽样帧，绿框逐帧在两半上找；
  分割那一半由 SegmentationInput.target_frames() 到用时再解码，segment_video 边读边写 jpg；
  MedSAM2 init_state 的读帧换成直接在存放设备上建张量（不改 MedSAM2 源码，结果逐位相同）；
  传播结果写进预分配数组。帧数最多的一段视频常驻内存峰值 11.2 GiB → 2.3 GiB，分辨率最大的
  一段原代码被 OOM 杀掉、现为 4.2 GiB；两段的掩码和全部产物与改前逐字节相同，33 段视频的
  第 1–2 步结果与改前一致，29 例配准与 review.csv 一致。
- 快照：ceus_quant 开跑时写 snapshot/（git、ceus.yaml、review.csv、uv.lock、segment.json），
  配置和核对表从快照副本读；收尾由新函数 runs.finish_snapshot 只新建 finished.json。
  build 与 ceus_align_review 同样改用 finish_snapshot 记结束时间。
- build：summary.json 加 video_sha256；装 CEUS 结果时核对快照里的 delivery_dir、逐例核对
  视频 SHA-256 和推注时间，不同就整次停下；新字段做类型检查，不进 tic.json。

来源：主会话任务（问题 1–3 及补充的 delivery_dir 比对）。

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>

tests/test_ceus_pipeline.py

@@ -24,14 +24,19 @@ from cadx.ceus import (
     CeusConfig,
     NoValidContourError,
     SegmentationInput,
+    VideoFile,
+    crop_frame,
     keyframe_images,
+    locate_contrast_side,
     pack_tic_curves,
     pack_trajectory,
     prepare_segmentation,
     quant_summary,
     quantify_case,
+    register_halves,
     render_case_overlay,
     render_tic_png,
+    split_views,
     tic_plot_markers,
     unpack_tic_curves,
     unpack_trajectory,
@@ -77,8 +82,9 @@ def test_prepare_segmentation_finds_contrast_half_and_maps_prompts(
     target = prepared.contrast.target_view
     assert (target.x1, target.x2) == (0, prepared.split_x)
     assert abs(prepared.split_x - SPLIT) <= 1
-    assert len(prepared.target_frames) == FRAMES
-    assert all(frame.shape == (target.height, target.width, 3) for frame in prepared.target_frames)
+    target_frames = list(prepared.target_frames())
+    assert len(target_frames) == FRAMES
+    assert all(frame.shape == (target.height, target.width, 3) for frame in target_frames)
     assert sorted(prepared.prompt_masks) == [p.frame_index for p in prepared.contrast.prompt_frames]
     assert 0 in prepared.prompt_masks
     xs = np.where(prepared.prompt_masks[0])[1]
@@ -87,6 +93,37 @@ def test_prepare_segmentation_finds_contrast_half_and_maps_prompts(
     assert abs(int(xs.max()) - 169) <= 5
 
 
+def test_streaming_prepare_matches_whole_video_in_memory(
+    prepared: SegmentationInput, config: CeusConfig
+) -> None:
+    """逐帧解码的第 1–2 步与「整段帧读进内存再交给各步」逐像素相同（改成流式之前就是后一种）。"""
+    frames = [frame for _, frame in VideoFile(prepared.video_path).iter_frames()]
+    split_x, left, right = split_views(frames, config.views)
+    registration = register_halves(
+        frames, left, right, config.registration, config.prompt_source, config.pan_source
+    )
+    contrast = locate_contrast_side(frames, left, right, config.prompt_source, config.keyframes)
+    assert prepared.split_x == split_x
+    assert prepared.registration == registration
+    assert prepared.contrast.side == contrast.side
+    assert (prepared.contrast.contrast_view, prepared.contrast.target_view) == (
+        contrast.contrast_view,
+        contrast.target_view,
+    )
+    assert [p.frame_index for p in prepared.contrast.prompt_frames] == [
+        p.frame_index for p in contrast.prompt_frames
+    ]
+    for ours, whole in zip(prepared.contrast.prompt_frames, contrast.prompt_frames, strict=True):
+        assert np.array_equal(ours.mask, whole.mask)
+    target_frames = list(prepared.target_frames())
+    assert len(target_frames) == len(frames)
+    for ours, frame in zip(target_frames, frames, strict=True):
+        assert np.array_equal(ours, crop_frame(frame, contrast.target_view))
+    assert np.array_equal(
+        prepared.first_contrast_frame, crop_frame(frames[0], contrast.contrast_view)
+    )
+
+
 def test_quantify_case_end_to_end(prepared: SegmentationInput, config: CeusConfig) -> None:
     result = quantify_case(prepared, _lesion_masks(prepared), _INJECTION_OFFSET_S, config)