diff --git a/dacapo/experiments/tasks/post_processors/watershed_post_processor.py b/dacapo/experiments/tasks/post_processors/watershed_post_processor.py
index fd22b426a..3f658d9ef 100644
--- a/dacapo/experiments/tasks/post_processors/watershed_post_processor.py
+++ b/dacapo/experiments/tasks/post_processors/watershed_post_processor.py
@@ -3,6 +3,10 @@
 from dacapo.blockwise.scheduler import segment_blockwise
 from dacapo.experiments.datasplits.datasets.arrays import ZarrArray
 from dacapo.store.array_store import LocalArrayIdentifier
+from dacapo.utils.array_utils import to_ndarray, save_ndarray
+from funlib.persistence import open_ds
+import daisy
+import mwatershed as mws
 
 from .watershed_post_processor_parameters import WatershedPostProcessorParameters
 from .post_processor import PostProcessor
@@ -123,29 +127,15 @@ def process(
             np.uint64,
             block_size * self.prediction_array.voxel_size,
         )
+        input_array = open_ds(
+            self.prediction_array_identifier.container.path,
+            self.prediction_array_identifier.dataset,
+        )
 
-        read_roi = Roi((0, 0, 0), self.prediction_array.voxel_size * block_size)
-        # run blockwise prediction
-        pars = {
-            "offsets": self.offsets,
-            "bias": parameters.bias,
-            "context": parameters.context,
-        }
-        segment_blockwise(
-            segment_function_file=str(
-                Path(Path(dacapo.blockwise.__file__).parent, "watershed_function.py")
-            ),
-            context=parameters.context,
-            total_roi=self.prediction_array.roi,
-            read_roi=read_roi.grow(parameters.context, parameters.context),
-            write_roi=read_roi,
-            num_workers=num_workers,
-            max_retries=2,  # TODO: make this an option
-            timeout=None,  # TODO: make this an option
-            ######
-            input_array_identifier=self.prediction_array_identifier,
-            output_array_identifier=output_array_identifier,
-            parameters=pars,
+        data = to_ndarray(input_array, output_array.roi)
+        segmentation = mws.agglom(
+            data - parameters.bias, offsets=self.offsets, randomized_strides=True
         )
+        save_ndarray(segmentation, self.prediction_array.roi, output_array)
 
-        return output_array
+        return output_array_identifier
diff --git a/docs/source/notebooks/minimal_tutorial.py b/docs/source/notebooks/minimal_tutorial.py
index d78b5b66a..411612f4d 100644
--- a/docs/source/notebooks/minimal_tutorial.py
+++ b/docs/source/notebooks/minimal_tutorial.py
@@ -376,3 +376,42 @@
     ax[snapshot, 2].imshow(prediction[prediction.shape[0] // 2])
     ax[snapshot, 0].set_ylabel(f"Snapshot {snapshot_it}")
 plt.show()
+
+# %%
+# Visualize validations
+import zarr
+
+num_validations = run_config.num_iterations // run_config.validation_interval
+fig, ax = plt.subplots(num_validations, 4, figsize=(10, 2 * num_validations))
+
+# Set column titles
+column_titles = ["Raw", "Ground Truth", "Prediction", "Segmentation"]
+for col in range(len(column_titles)):
+    ax[0, col].set_title(column_titles[col])
+
+for validation in range(1, num_validations + 1):
+    dataset = run.datasplit.validate[0].name
+    validation_it = validation * run_config.validation_interval
+    # break
+    raw = zarr.open(
+        f"/Users/pattonw/dacapo/example_run/validation.zarr/inputs/{dataset}/raw"
+    )[:]
+    gt = zarr.open(
+        f"/Users/pattonw/dacapo/example_run/validation.zarr/inputs/{dataset}/gt"
+    )[0]
+    pred_path = f"/Users/pattonw/dacapo/example_run/validation.zarr/{validation_it}/ds_{dataset}/prediction"
+    out_path = f"/Users/pattonw/dacapo/example_run/validation.zarr/{validation_it}/ds_{dataset}/output/WatershedPostProcessorParameters(id=2, bias=0.5, context=(32, 32, 32))"
+    output = zarr.open(
+        out_path
+    )[:]
+    prediction = zarr.open(pred_path)[0]
+    print(raw.shape, gt.shape, output.shape)
+    c = (raw.shape[1] - gt.shape[1]) // 2
+    if c != 0:
+        raw = raw[:, c:-c, c:-c]
+    ax[validation - 1, 0].imshow(raw[raw.shape[0] // 2])
+    ax[validation - 1, 1].imshow(gt[gt.shape[0] // 2])
+    ax[validation - 1, 2].imshow(prediction[prediction.shape[0] // 2])
+    ax[validation - 1, 3].imshow(output[output.shape[0] // 2])
+    ax[validation - 1, 0].set_ylabel(f"Validation {validation_it}")
+plt.show()
diff --git a/pyproject.toml b/pyproject.toml
index ade6bb47c..866c9fffe 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -78,6 +78,8 @@ docs = [
     "sphinx-click",
     "sphinx-rtd-theme",
     "myst-parser",
+    "matplotlib",
+    "pooch",
 ]
 examples = [
     "ipython",