From 5aca68af4c6ca5d8ba29b2ecc7253889b44cdc43 Mon Sep 17 00:00:00 2001
From: Christopher Rhodes <christopher.rhodes@embl.de>
Date: Wed, 18 Oct 2023 14:54:05 +0200
Subject: [PATCH] Needed to make copy of project file
---
...fer_labels_to_ilastik_object_classifier.py | 21 ++++++++++++-------
1 file changed, 13 insertions(+), 8 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 a02840be..f3b5a5bc 100644
--- a/extensions/chaeo/examples/transfer_labels_to_ilastik_object_classifier.py
+++ b/extensions/chaeo/examples/transfer_labels_to_ilastik_object_classifier.py
@@ -203,7 +203,7 @@ 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-20231018-0000'
+ where_patch_stack = root / 'exp0009/output/labeled_patches-20231018-0001'
# auto-populate an object classifier
new_ilp = generate_ilastik_object_classifier(
@@ -212,11 +212,11 @@ if __name__ == '__main__':
stack_name='train'
)
- def infer_and_compare(suffix):
+ def infer_and_compare(ilp, suffix):
# infer object labels from the same data used to train the classifier
train_zstack_raw = generate_file_accessor(where_patch_stack / 'zstack_train_raw.tif')
train_zstack_mask = generate_file_accessor(where_patch_stack / 'zstack_train_mask.tif')
- mod = PatchStackObjectClassifier({'project_file': where_patch_stack / new_ilp})
+ mod = PatchStackObjectClassifier({'project_file': where_patch_stack / ilp})
result_acc, _ = mod.infer(train_zstack_raw, train_zstack_mask)
write_accessor_data_to_file(where_patch_stack / f'zstack_train_result_{suffix}.tif', result_acc)
@@ -229,17 +229,22 @@ if __name__ == '__main__':
),
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('before')
+ infer_and_compare(new_ilp, 'before')
- # prompt user input when ilastik file has been modified in-app
- print(f'Press enter when project file {new_ilp} has been updated in ilastik')
+ # 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')
+ )
+ print(f'Press enter when project file {mod_ilp} has been updated in ilastik')
input()
- # repeat inference with the same project file, but a fresh model handle
- infer_and_compare('after')
+ # repeat inference with the modified project file
+ infer_and_compare(mod_ilp, 'after')
--
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