From ed29f8f69b7bbbda005266ae7d749daa39f86996 Mon Sep 17 00:00:00 2001
From: Christopher Rhodes <christopher.rhodes@embl.de>
Date: Mon, 16 Oct 2023 11:12:27 +0200
Subject: [PATCH] Start end-to-end transfer method to ilastik object model
---
extensions/chaeo/examples/label_patches.py | 2 +
...fer_labels_to_ilastik_object_classifier.py | 56 ++++++++++++++++++-
2 files changed, 56 insertions(+), 2 deletions(-)
diff --git a/extensions/chaeo/examples/label_patches.py b/extensions/chaeo/examples/label_patches.py
index 04f2c00c..fe877e45 100644
--- a/extensions/chaeo/examples/label_patches.py
+++ b/extensions/chaeo/examples/label_patches.py
@@ -13,3 +13,5 @@ if __name__ == '__main__':
where_output=autonumber_new_directory(root, 'labeled_patches'),
)
print('Finished')
+
+
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 9d5c273e..7b61d580 100644
--- a/extensions/chaeo/examples/transfer_labels_to_ilastik_object_classifier.py
+++ b/extensions/chaeo/examples/transfer_labels_to_ilastik_object_classifier.py
@@ -4,8 +4,22 @@ import h5py
import ilastik.applets.objectClassification
import numpy as np
import pandas as pd
+import tifffile
from extensions.ilastik.models import IlastikObjectClassifierModel
+from model_server.accessors import generate_file_accessor
+
+def get_dataset_info(h5):
+ lane = 'Input Data/infos/lane0000'
+ info = {}
+ for gk in ['Raw Data', 'Segmentation Image']:
+ info[gk] = {}
+ for dk in ['location', 'filePath', 'shape']:
+ try:
+ info[gk][dk] = h5[f'{lane}/{gk}/{dk}'][()]
+ except Exception as e:
+ print(e)
+ return info
def transfer_labels_to_ilastik_ilp(ilp, df_stack_meta):
@@ -22,6 +36,9 @@ def transfer_labels_to_ilastik_ilp(ilp, df_stack_meta):
hf.write(f'{line[0]} --- {line[1]}\n')
h5.visititems(lambda k, v: print(k + ' : ' + str(v)))
+ # put certain h5 groups in scope
+ h5info = get_dataset_info(h5)
+
# change key of label names
ln = ['none'] + list(df_stack_meta.sort_values('annotation_class_id').annotation_class.unique())
del h5['ObjectClassification/LabelNames']
@@ -39,9 +56,44 @@ def transfer_labels_to_ilastik_ilp(ilp, df_stack_meta):
ds[1] = float(df_stack_meta.loc[df_stack_meta.zi == idx, 'annotation_class_id'].iat[0])
print(f'Changed label {ti} from {la_old} to {ds[1]}')
+def generate_ilastik_object_classifier(template_ilp, where_training: str):
+
+ # validate input data
+ where = Path(where_training)
+ zstacks = {
+ 'raw': {
+ 'path': where / 'zstack_train_raw.tif',
+ },
+ 'seg': {
+ 'path': where / 'zstack_train_mask.tif',
+ }
+ }
+
+ for k, v in zstacks.items():
+ # assert v['path'].exists(), 'Could not find input z-stack: ' + v['path']
+ # ff = tifffile.imread(v['path'])
+ # v['nz'] = ff.shape[0]
+ # v['hw'] = ff.shape[1:2]
+ # v['dtype'] = ff.dtype
+ v['acc'] = generate_file_accessor(v['path'])
+ assert zstacks['raw']['acc'].is_binary()
+
+ assert zstacks['raw']
+
+ with h5py.File(template_ilp, 'r+') as h5:
+ pass
+
+
if __name__ == '__main__':
- ilp = 'c:/Users/rhodes/model-server/ilastik/test_autolabel_obj.ilp'
+ ilp = 'c:/Users/rhodes/model-server/ilastik/test_autolabel_obj - Copy.ilp'
+ # ilp = 'c:/Users/rhodes/model-server/ilastik/test_template_obj.ilp'
+
df = pd.read_csv(
'c:/Users/rhodes/projects/proj0011-plankton-seg/exp0009/output/labeled_patches-20231014-0002/train_stack.csv'
)
- transfer_labels_to_ilastik_ilp(ilp, df)
\ No newline at end of file
+ # transfer_labels_to_ilastik_ilp(ilp, df)
+
+ generate_ilastik_object_classifier(
+ ilp,
+ 'c:/Users/rhodes/projects/proj0011-plankton-seg/exp0009/output/labeled_patches-20231014-0002'
+ )
\ No newline at end of file
--
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