Show orthogonal CT triplets in common model space

app.py

@@ -321,6 +321,36 @@ def render_three_views(volume_xyz: np.ndarray, title: str) -> None:
             render_image(get_slice(volume_xyz, plane, index), f"{cn_name} #{index}")
 
 
+def render_three_way_views(fixed_xyz: np.ndarray, moving_xyz: np.ndarray, warped_xyz: np.ndarray | None) -> None:
+    if warped_xyz is None:
+        fixed_xyz, moving_xyz = crop_to_common_shape(fixed_xyz, moving_xyz)
+        volumes = [("固定图像", fixed_xyz), ("移动图像", moving_xyz), ("配准后图像", None)]
+        st.warning("尚未生成配准后图像。")
+    else:
+        fixed_xyz, moving_xyz, warped_xyz = crop_to_common_shape(fixed_xyz, moving_xyz, warped_xyz)
+        volumes = [("固定图像", fixed_xyz), ("移动图像", moving_xyz), ("配准后图像", warped_xyz)]
+
+    st.caption(f"显示尺寸：{fixed_xyz.shape[0]} x {fixed_xyz.shape[1]} x {fixed_xyz.shape[2]}")
+    planes = [("Axial", "轴状面"), ("Coronal", "冠状面"), ("Sagittal", "矢状面")]
+    for plane, cn_name in planes:
+        axis = plane_axis(plane)
+        index = st.slider(
+            f"{cn_name}切片",
+            0,
+            fixed_xyz.shape[axis] - 1,
+            fixed_xyz.shape[axis] // 2,
+            key=f"three-way-{plane}",
+        )
+        st.markdown(f"#### {cn_name}")
+        columns = st.columns(3)
+        for col, (label, volume) in zip(columns, volumes):
+            with col:
+                if volume is None:
+                    st.info("待生成")
+                else:
+                    render_image(get_slice(volume, plane, index), f"{label} #{index}")
+
+
 def render_overlay_views(fixed_xyz: np.ndarray, warped_xyz: np.ndarray) -> None:
     fixed_xyz, warped_xyz = crop_to_common_shape(fixed_xyz, warped_xyz)
     mode = st.radio("对比模式", ["Alpha 融合", "棋盘格"], horizontal=True)
@@ -535,12 +565,38 @@ def render_metric_charts(fixed_xyz: np.ndarray, moving_xyz: np.ndarray, warped_x
 def load_result_paths(out_dir: str) -> Dict[str, str]:
     out = Path(out_dir)
     return {
+        "prepared_moving": str(out / "moving_model_input.nii.gz"),
+        "prepared_fixed": str(out / "fixed_model_input.nii.gz"),
         "warped": str(out / "warped_moving.nii.gz"),
         "ddf": str(out / "ddf_mm.nii.gz"),
         "metrics": str(out / "metrics.json"),
     }
 
 
+def read_json_dict(path: str | Path) -> Dict:
+    path = Path(path)
+    if not path.exists():
+        return {}
+    try:
+        data = json.loads(path.read_text(encoding="utf-8"))
+    except Exception:
+        return {}
+    return data if isinstance(data, dict) else {}
+
+
+def same_path(left: str | Path | None, right: str | Path | None) -> bool:
+    if not left or not right:
+        return False
+    try:
+        return Path(left).expanduser().resolve(strict=False) == Path(right).expanduser().resolve(strict=False)
+    except Exception:
+        return str(left) == str(right)
+
+
+def result_matches_inputs(result: Dict, moving_path: str, fixed_path: str) -> bool:
+    return same_path(result.get("moving_path"), moving_path) and same_path(result.get("fixed_path"), fixed_path)
+
+
 def run_inference_from_ui(moving_path: str, fixed_path: str, checkpoint_path: str, out_dir: str) -> Dict:
     from infer import run_inference
 
@@ -580,19 +636,35 @@ def main() -> None:
 
     result_paths = load_result_paths(out_dir)
     last_result = st.session_state.get("last_result", {})
-    warped_path = str(last_result.get("warped_path", result_paths["warped"]))
-    ddf_path = str(last_result.get("ddf_path", result_paths["ddf"]))
     metrics_path = str(last_result.get("metrics_path", result_paths["metrics"]))
+    saved_result = read_json_dict(metrics_path)
+    result_info = {**saved_result, **last_result}
+    outputs_current = result_matches_inputs(result_info, moving_path, fixed_path)
+
+    prepared_moving_path = str(result_info.get("prepared_moving_path", result_paths["prepared_moving"]))
+    prepared_fixed_path = str(result_info.get("prepared_fixed_path", result_paths["prepared_fixed"]))
+    if outputs_current:
+        warped_path = str(result_info.get("warped_path", result_paths["warped"]))
+        ddf_path = str(result_info.get("ddf_path", result_paths["ddf"]))
+        display_moving_path = prepared_moving_path if Path(prepared_moving_path).exists() else moving_path
+        display_fixed_path = prepared_fixed_path if Path(prepared_fixed_path).exists() else fixed_path
+    else:
+        warped_path = ""
+        ddf_path = ""
+        display_moving_path = moving_path
+        display_fixed_path = fixed_path
 
     status_cols = st.columns(4)
-    status_cols[0].metric("Moving", "存在" if Path(moving_path).exists() else "缺失")
-    status_cols[1].metric("Fixed", "存在" if Path(fixed_path).exists() else "缺失")
+    status_cols[0].metric("Moving", "存在" if Path(display_moving_path).exists() else "缺失")
+    status_cols[1].metric("Fixed", "存在" if Path(display_fixed_path).exists() else "缺失")
     status_cols[2].metric("Warped", "存在" if Path(warped_path).exists() else "缺失")
     status_cols[3].metric("DDF", "存在" if Path(ddf_path).exists() else "缺失")
+    if result_info and not outputs_current:
+        st.warning("输出目录中的历史结果与当前输入不匹配，请重新开始推理。")
 
     try:
-        moving_xyz, moving_spacing, moving_stride = load_nifti_cached(moving_path, max_voxels=display_max_voxels)
-        fixed_xyz, fixed_spacing, fixed_stride = load_nifti_cached(fixed_path, max_voxels=display_max_voxels)
+        moving_xyz, moving_spacing, moving_stride = load_nifti_cached(display_moving_path, max_voxels=display_max_voxels)
+        fixed_xyz, fixed_spacing, fixed_stride = load_nifti_cached(display_fixed_path, max_voxels=display_max_voxels)
     except Exception as exc:
         st.warning(f"待显示数据尚未就绪: {exc}")
         return
@@ -615,15 +687,7 @@ def main() -> None:
 
     tab_views, tab_overlay, tab_ddf, tab_metrics = st.tabs(["正交三视图", "重叠对比", "形变场", "量化图"])
     with tab_views:
-        view_target = st.radio("显示对象", ["固定图像", "移动图像", "配准后图像"], horizontal=True)
-        if view_target == "固定图像":
-            render_three_views(fixed_xyz, "固定图像")
-        elif view_target == "移动图像":
-            render_three_views(moving_xyz, "移动图像")
-        elif warped_xyz is not None:
-            render_three_views(warped_xyz, "配准后图像")
-        else:
-            st.warning("尚未生成配准后图像。")
+        render_three_way_views(fixed_xyz, moving_xyz, warped_xyz)
 
     with tab_overlay:
         if warped_xyz is None: