6002459992

Committed 28 Aug 2023 04:33PM UTC coverage: 80.919%. Remained the same

Build # 6002459992

Build Type

push

github

Committed by

web-flow

Commit Message

Update README.md

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/src/cell_classification/prepare_data_script_MSK_pancreas.py

import os

from cell_classification.simple_data_prep import SimpleTFRecords

os.environ["CUDA_VISIBLE_DEVICES"] = "-1"


def naming_convention(fname):
    return os.path.join(
        "E:/angelo_lab/data/MSKCC_pancreas/segmentation",
        fname + "feature_0.ome.tif"
    )


data_prep = SimpleTFRecords(
    data_dir=os.path.normpath(
        "E:/angelo_lab/data/MSKCC_pancreas/raw_structured"
    ),
    cell_table_path=os.path.normpath(
        "E:/angelo_lab/data/MSKCC_pancreas/cell_table.csv"
    ),
    imaging_platform="Vectra",
    dataset="MSK_pancreas",
    tissue_type="pancreas",
    nuclei_channels=["DAPI"],
    membrane_channels=["CD8", "CD40", "CD40-L", "panCK"],
    tile_size=[256, 256],
    stride=[240, 240],
    tf_record_path=os.path.normpath("E:/angelo_lab/data/MSKCC_pancreas"),
    normalization_quantile=0.999,
    selected_markers=["CD8", "CD40", "CD40-L", "panCK", "PD-1", "PD-L1"],
    sample_key="fov",
    segment_label_key="labels",
    segmentation_naming_convention=naming_convention,
    exclude_background_tiles=True,
    img_suffix=".ome.tif",
    gt_suffix="",
    normalization_dict_path=os.path.normpath(
        "E:/angelo_lab/data/MSKCC_pancreas/normalization_dict.json"
    ),
)

data_prep.make_tf_record()

1	import os	×
2
3	from cell_classification.simple_data_prep import SimpleTFRecords	×
4
5	os.environ["CUDA_VISIBLE_DEVICES"] = "-1"	×
6
7
8	def naming_convention(fname):	×
9	return os.path.join(	×
10	"E:/angelo_lab/data/MSKCC_pancreas/segmentation",
11	fname + "feature_0.ome.tif"
12	)
13
14
15	data_prep = SimpleTFRecords(	×
16	data_dir=os.path.normpath(
17	"E:/angelo_lab/data/MSKCC_pancreas/raw_structured"
18	),
19	cell_table_path=os.path.normpath(
20	"E:/angelo_lab/data/MSKCC_pancreas/cell_table.csv"
21	),
22	imaging_platform="Vectra",
23	dataset="MSK_pancreas",
24	tissue_type="pancreas",
25	nuclei_channels=["DAPI"],
26	membrane_channels=["CD8", "CD40", "CD40-L", "panCK"],
27	tile_size=[256, 256],
28	stride=[240, 240],
29	tf_record_path=os.path.normpath("E:/angelo_lab/data/MSKCC_pancreas"),
30	normalization_quantile=0.999,
31	selected_markers=["CD8", "CD40", "CD40-L", "panCK", "PD-1", "PD-L1"],
32	sample_key="fov",
33	segment_label_key="labels",
34	segmentation_naming_convention=naming_convention,
35	exclude_background_tiles=True,
36	img_suffix=".ome.tif",
37	gt_suffix="",
38	normalization_dict_path=os.path.normpath(
39	"E:/angelo_lab/data/MSKCC_pancreas/normalization_dict.json"
40	),
41	)
42
43	data_prep.make_tf_record()	×

angelolab / cell_classification / 6002459992

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