From b8bd1a91c86e8a27e63a9f30b78e872f527bceb0 Mon Sep 17 00:00:00 2001
From: Christopher Rhodes <christopher.rhodes@embl.de>
Date: Wed, 18 Oct 2023 15:23:54 +0200
Subject: [PATCH] Renamed a few output files
---
...fer_labels_to_ilastik_object_classifier.py | 36 +++++++++----------
1 file changed, 17 insertions(+), 19 deletions(-)
diff --git a/extensions/chaeo/examples/transfer_labels_to_ilastik_object_classifier.py b/extensions/chaeo/examples/transfer_labels_to_ilastik_object_classifier.py
index f3b5a5bc..6dd5e27d 100644
--- a/extensions/chaeo/examples/transfer_labels_to_ilastik_object_classifier.py
+++ b/extensions/chaeo/examples/transfer_labels_to_ilastik_object_classifier.py
@@ -8,7 +8,6 @@ import skimage
import uuid
import vigra
-from extensions.chaeo.util import autonumber_new_file
from extensions.ilastik.models import IlastikObjectClassifierFromSegmentationModel
from model_server.accessors import generate_file_accessor, GenericImageDataAccessor, InMemoryDataAccessor, write_accessor_data_to_file
@@ -88,7 +87,13 @@ def get_dataset_info(h5: h5py.File, lane : int = 0):
return info
-def generate_ilastik_object_classifier(template_ilp: str, where: str, stack_name: str = 'train', lane: int = 0):
+def generate_ilastik_object_classifier(
+ template_ilp: str,
+ where: str,
+ stack_name: str = 'train',
+ lane: int = 0,
+ proj_name='auto_obj'
+):
"""
Starting with a template project file, transfer input data and labels to a duplicate project file.
@@ -134,11 +139,11 @@ def generate_ilastik_object_classifier(template_ilp: str, where: str, stack_name
assert info[hg]['location'] == b'FileSystem'
assert info[hg]['axes'] == ['t', 'y', 'x']
- new_ilp = shutil.copy(template_ilp, root / autonumber_new_file(root, 'auto-obj', 'ilp'))
+ new_ilp = shutil.copy(template_ilp, where / (proj_name + '.ilp'))
# write to new project file
lns = f'{lane:04d}'
- with h5py.File(new_ilp, 'r+') as h5:
+ with h5py.File(where / new_ilp, 'r+') as h5:
def set_ds(grp, ds, val):
ds = h5[f'Input Data/infos/lane{lns}/{grp}/{ds}']
ds[()] = val
@@ -193,7 +198,7 @@ def compare_object_maps(truth: GenericImageDataAccessor, inferred: GenericImageD
ob_id = skimage.measure.label(inf_img)
pr = skimage.measure.regionprops_table(ob_id, properties=['label', 'area'])
mask = inf_img == pr['label'][pr['area'].argmax()]
- dd['inferred_label'] = np.unique(mask * inf_img)[1]
+ dd['inferred_label'] = np.unique(mask * inf_img)[-1] # occasionally no object in frame
dd['multiples'] = True
else: # exactly one unique object class in frame
dd['inferred_label'] = unique[1]
@@ -203,13 +208,14 @@ def compare_object_maps(truth: GenericImageDataAccessor, inferred: GenericImageD
if __name__ == '__main__':
root = Path('c:/Users/rhodes/projects/proj0011-plankton-seg/')
template_ilp = root / 'exp0014/template_obj.ilp'
- where_patch_stack = root / 'exp0009/output/labeled_patches-20231018-0001'
+ where_patch_stack = root / 'exp0009/output/labeled_patches-20231018-0005'
# auto-populate an object classifier
- new_ilp = generate_ilastik_object_classifier(
+ auto_ilp = generate_ilastik_object_classifier(
template_ilp,
where_patch_stack,
- stack_name='train'
+ stack_name='train',
+ proj_name='auto_obj_before'
)
def infer_and_compare(ilp, suffix):
@@ -223,24 +229,16 @@ if __name__ == '__main__':
# write comparison tables
train_truth_labels = generate_file_accessor(where_patch_stack / f'zstack_train_label.tif')
df_comp = compare_object_maps(train_truth_labels, result_acc)
- df_comp.to_csv(
- where_patch_stack / autonumber_new_file(
- where_patch_stack, f'compare_train_result_{suffix}', 'csv'
- ),
- index=False
- )
+ df_comp.to_csv(where_patch_stack / f'compare_train_result_{suffix}.csv', index=False)
print(f'Generated ilastik project {ilp}')
print('Truth and inferred labels match?')
print(pd.value_counts(df_comp['truth_label'] == df_comp['inferred_label']))
# infer object labels from the same data used to train the classifier
- infer_and_compare(new_ilp, 'before')
+ infer_and_compare(auto_ilp, 'before')
# copy project and prompt user input once ilastik file has been modified in-app
- mod_ilp = shutil.copy(
- new_ilp,
- where_patch_stack / autonumber_new_file(where_patch_stack, 'auto-obj', 'ilp')
- )
+ mod_ilp = shutil.copy(auto_ilp, where_patch_stack / 'auto_obj_after.ilp')
print(f'Press enter when project file {mod_ilp} has been updated in ilastik')
input()
--
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