Merge pull request #190 from AllenNeuralDynamics/seanf-fusion/multiscale

Fixed translation fusion collision bug

Author: seanfite-alleninstitute

Rhapso/pipelines/ray/aws/fusion_pipeline.py

@@ -35,6 +35,7 @@
     "from Rhapso.pipelines.ray.multiscale import MultiScale\n"
     f"cfg = json.loads(base64.b64decode(\\\"{serialized_config}\\\").decode())\n"
     "ms = MultiScale(\n"
+    "    xml_path=cfg[\\\"xml_path_multiscale\\\"],\n"
     "    zarr_path=cfg[\\\"multiscale_zarr_path\\\"],\n"
     "    chunk_size=cfg[\\\"multiscale_chunk_size\\\"],\n"
     "    n_lvls=cfg[\\\"n_lvls\\\"],\n"

Rhapso/pipelines/ray/local/fusion_pipeline.py

@@ -3,7 +3,7 @@
 import yaml
 
 # Point to param file
-with open("Rhapso/pipelines/ray/param/fusion/HCR_000000-s40.yml", "r") as file:
+with open("Rhapso/pipelines/ray/param/fusion/HCR_823476.yml", "r") as file:
     config = yaml.safe_load(file)
 
 # FUSION
@@ -28,5 +28,5 @@
 )
 
 # Run pipeline
-fusion.execute_job()
+# fusion.execute_job()
 multiscale.run()

Rhapso/pipelines/ray/param/fusion/HCR_823476.yml

@@ -1,15 +1,16 @@
 # AFFINE FUSION
 # -----------------------------------
-xml_path_translation_fusion: "s3://aind-open-data/HCR_823476-s1-ls2_2025-11-18_00-00-00_processed_2026-02-25_18-17-21/image_tile_alignment/bigstitcher.xml"
-input_path_translation_fusion: "s3://aind-open-data/HCR_823476-s1-ls2_2025-11-18_00-00-00_processed_2026-02-25_18-17-21/image_radial_correction/"
-output_s3_path_translation_fusion: "s3://aind-scratch-data/sean.fite/HCR_823476_s5_11-18-t1/fusion/fused.zarr"
+xml_path_translation_fusion: "s3://aind-open-data/HCR_823476-s1-ls2_2025-11-18_00-00-00_processed_2026-03-03_22-58-55/image_tile_alignment/bigstitcher.xml"
+input_path_translation_fusion: "s3://aind-open-data/HCR_823476-s1-ls2_2025-11-18_00-00-00_processed_2026-03-03_22-58-55/image_radial_correction/"
+output_s3_path_translation_fusion: "s3://aind-scratch-data/sean.fite/HCR_823476-11-18-t1/fusion/fused.zarr"
 channel: 488
 default_chunk_size: [1, 1, 128, 128, 128]
-cpu_cell_size: [256, 256, 256]
+cpu_cell_size: [640, 256, 256]
 
 # MULTISCALE
 # -----------------------------------
-multiscale_zarr_path: "s3://aind-scratch-data/sean.fite/HCR_823476_s5_12-24/channel_488.zarr/multiscale_fused"
+xml_path_multiscale: "s3://aind-open-data/HCR_823476-s1-ls2_2025-11-18_00-00-00_processed_2026-03-03_22-58-55/image_tile_alignment/bigstitcher.xml"
+multiscale_zarr_path: "s3://aind-scratch-data/sean.fite/HCR_823476-11-18-t1/fusion/fused.zarr"
 multiscale_chunk_size: [128, 128, 128]
 n_lvls: 6                                                              # Including base level
 scale_factor: [[1, 2, 2], [1, 2, 2], [2, 2, 2], [2, 2, 2], [2, 2, 2]]  # ZYX

Rhapso/translation_fusion/fusion.py

@@ -546,7 +546,7 @@ def cpu_fusion(
 
     total = time.perf_counter() - t_total0
     # print(f"[cpu_fusion] pid={os.getpid()} DONE blend={t_blend:.3f}s write={t_write:.3f}s total={total:.3f}s", flush=True)
-
+    
 class FusionVolumeSampler(cq.VolumeSampler):
     def __init__(
         self,
@@ -622,8 +622,8 @@ def __init__(
         for t_id, o_ids in tile_to_overlap_ids.items():
             # This is the base nullspace
             t_aabb = list(self.tile_aabbs[t_id])
-            # t_aabb[0] = 0
-            # t_aabb[1] = output_volume_size[0]
+            t_aabb[0] = 0
+            t_aabb[1] = output_volume_size[0]
 
             for o_id in o_ids:
                 o_aabb = modified_overlaps[o_id]
@@ -696,36 +696,34 @@ def __init__(
 
     def _check_true_collision(
         self,
-        cell_box: geometry.AABB,
-        transform_list: list[geometry.Transform],
+        cell_box: "geometry.AABB",
+        transform_list: list["geometry.Transform"],
         src_vol_shape_zyx: tuple[int, int, int],
     ) -> bool:
-        # Build the 8 corners (zyx) with +/-0.5 offsets
         z_min, z_max, y_min, y_max, x_min, x_max = cell_box
+
+        # sample at voxel centers: (min+0.5, max-0.5) on each axis
         zs = np.array([z_min + 0.5, z_max - 0.5], dtype=np.float32)
         ys = np.array([y_min + 0.5, y_max - 0.5], dtype=np.float32)
         xs = np.array([x_min + 0.5, x_max - 0.5], dtype=np.float32)
 
-        cell_box_pts = np.array(
-            [[z, y, x] for z in zs for y in ys for x in xs],
-            dtype=np.float32
-        )  # (8, 3)
+        # 2x2x2 grid of corners, shape (2,2,2,3) in ZYX order
+        z_grid, y_grid, x_grid = np.meshgrid(zs, ys, xs, indexing="ij")
+        cell_box_pts = np.stack([z_grid, y_grid, x_grid], axis=-1).astype(np.float32)
 
-        # Apply origin
-        cell_box_pts += np.asarray(self.output_volume_origin, dtype=np.float32).reshape(1, 3)
+        # move into output/global space
+        cell_box_pts = cell_box_pts + np.asarray(self.output_volume_origin, dtype=np.float32)
 
-        # Apply inverse transforms (NumPy)
+        # apply inverse transforms in reverse order
         for tfm in reversed(transform_list):
+            # assumes tfm.backward can accept numpy arrays; if not, see note below
             cell_box_pts = tfm.backward_np(cell_box_pts)
 
-        # AABB of transformed points (zyx)
-        z0, z1 = float(cell_box_pts[:, 0].min()), float(cell_box_pts[:, 0].max())
-        y0, y1 = float(cell_box_pts[:, 1].min()), float(cell_box_pts[:, 1].max())
-        x0, x1 = float(cell_box_pts[:, 2].min()), float(cell_box_pts[:, 2].max())
-        cell_box_src: geometry.AABB = (z0, z1, y0, y1, x0, x1)
+        # compute AABB in source space
+        cell_box_src: "geometry.AABB" = geometry.aabb_3d_np(cell_box_pts)
 
         sv_z, sv_y, sv_x = src_vol_shape_zyx
-        aabb_src: geometry.AABB = (0, sv_z, 0, sv_y, 0, sv_x)
+        aabb_src: "geometry.AABB" = (0, sv_z, 0, sv_y, 0, sv_x)
 
         return utils.check_collision(cell_box_src, aabb_src)
 
@@ -788,4 +786,4 @@ def __iter__(self):
                         stride_condition = (cell_num % self.stride == self.start)
 
                         if true_overlap_condition and stride_condition:
-                            yield curr_cell, src_ids
+                            yield curr_cell, src_ids