Add check for validation data

analysis/validation/check_validation.py

+import h5py
+from heimdall import view, to_source
+
+
+def check_cell_evaluation():
+    from scripts.segmentation.validation.eval_cells import (eval_slice,
+                                                            get_ignore_seg_ids,
+                                                            get_bounding_box)
+
+    praw = '../../data'
+    pseg = '../../data'
+    pann = '../../data'
+
+    table_path = '../../data'
+    ignore_seg_ids = get_ignore_seg_ids(table_path)
+
+    with h5py.File(pseg, 'r') as fseg, h5py.File(pann, 'r') as fann:
+        ds_seg = fseg['t00000/s00/0/cells']
+        ds_ann = fann['xy/']
+
+        print("Run evaluation ...")
+        res, masks = eval_slice(ds_seg, ds_ann, ignore_seg_ids, min_radius=16,
+                                return_maksks=True)
+        fm, fs = masks['false_merges'], masks['false_splits']
+        print()
+        print("Eval result")
+        print(res)
+        print()
+
+        print("Load raw data ...")
+        bb = get_bounding_box(ds_ann)
+        with h5py.File(praw, 'r') as f:
+            raw = f['t00000/s00/1/cells'][bb]
+
+        print("Load seg data ...")
+        seg = ds_seg[bb].squeeze()
+
+        view(to_source(raw, name='raw'), to_source(seg, name='seg'),
+             to_source(fm, name='merges'), to_source(fs, name='splits'))
+
+
+# def check_nucleus_evaluation():
+#     eval_nuclei()
+
+
+if __name__ == '__main__':
+    check_cell_evaluation()

scripts/segmentation/validation/eval_cells.py

@@ -5,16 +5,22 @@ from elf.io import open_file, is_dataset
 from .evaluate_annotations import evaluate_annotations, merge_evaluations
 
 
-def eval_slice(ds_seg, ds_ann, ignore_seg_ids, min_radius):
-    ds_seg.n_threads = 8
-    ds_ann.n_threads = 8
-
-    attrs = ds_ann.attrs
+def get_bounding_box(ds):
+    attrs = ds.attrs
     start, stop = attrs['starts'], attrs['stops']
     bb = tuple(slice(sta, sto) for sta, sto in zip(start, stop))
+    return bb
+
+
+def eval_slice(ds_seg, ds_ann, ignore_seg_ids, min_radius,
+               return_masks=False):
+    ds_seg.n_threads = 8
+    ds_ann.n_threads = 8
 
+    bb = get_bounding_box(ds_ann)
     annotations = ds_ann[:]
     seg = ds_seg[bb].squeeze()
+    assert annotations.shape == seg.shape
 
     seg_eval = vigra.analysis.labelImageWithBackground(seg)
 
@@ -28,7 +34,8 @@ def eval_slice(ds_seg, ds_ann, ignore_seg_ids, min_radius):
     bg_annotations = annotations == 3
 
     return evaluate_annotations(seg_eval, fg_annotations, bg_annotations,
-                                this_ignore_ids, min_radius=min_radius)
+                                this_ignore_ids, min_radius=min_radius,
+                                return_masks=return_masks)
 
 
 def get_ignore_seg_ids(table_path, ignore_names=['cuticle', 'neuropil', 'yolk']):
@@ -55,8 +62,11 @@ def eval_cells(seg_path, seg_key,
         def visit_annotation(name, node):
             nonlocal eval_res
             if is_dataset(node):
+                print("Evaluating:", name)
                 res = eval_slice(ds_seg, node, ignore_seg_ids, min_radius)
                 eval_res = merge_evaluations(res, eval_res)
+            else:
+                print("Group:", name)
 
         g.visititems(visit_annotation)