From 1092b9c55d898912c82ecb14ed64bee6b239b108 Mon Sep 17 00:00:00 2001
From: Christopher Rhodes <christopher.rhodes@embl.de>
Date: Thu, 5 Oct 2023 15:25:29 +0200
Subject: [PATCH] Tested operation to flatten image based on focal points from
body mask
---
.../chaeo/examples/batch_run_patches.py | 2 +-
extensions/chaeo/tests/test_zstack.py | 24 +++++++++
extensions/chaeo/workflows.py | 10 ++++
extensions/chaeo/zmask.py | 50 ++++++++++++++++++-
4 files changed, 84 insertions(+), 2 deletions(-)
diff --git a/extensions/chaeo/examples/batch_run_patches.py b/extensions/chaeo/examples/batch_run_patches.py
index cebc0b40..fb96be1a 100644
--- a/extensions/chaeo/examples/batch_run_patches.py
+++ b/extensions/chaeo/examples/batch_run_patches.py
@@ -51,7 +51,7 @@ if __name__ == '__main__':
}
result = export_patches_from_multichannel_zstack(**export_kwargs)
-
+ break
# parse and record results
df = result['dataframe']
df['filename'] = ff.name
diff --git a/extensions/chaeo/tests/test_zstack.py b/extensions/chaeo/tests/test_zstack.py
index f2394889..39da79b5 100644
--- a/extensions/chaeo/tests/test_zstack.py
+++ b/extensions/chaeo/tests/test_zstack.py
@@ -91,3 +91,27 @@ class TestZStackDerivedDataProducts(unittest.TestCase):
make_3d=True)
self.assertGreaterEqual(len(files), 1)
+ def test_flatten_image(self):
+ zmask, meta, df, interm = build_zmask_from_object_mask(
+ self.obmap.get_one_channel_data(0),
+ self.stack.get_one_channel_data(1),
+ mask_type='boxes',
+ )
+
+ from extensions.chaeo.zmask import project_stack_from_focal_points
+
+ dff = df[df['keeper'] == True]
+
+ img = project_stack_from_focal_points(
+ dff['centroid-0'].to_numpy(),
+ dff['centroid-1'].to_numpy(),
+ dff['zi'].to_numpy(),
+ self.stack.get_one_channel_data(1),
+ )
+
+ self.assertEqual(img.shape[0:2], self.stack.shape[0:2])
+
+ write_accessor_data_to_file(
+ output_path / 'flattened.tif',
+ InMemoryDataAccessor(img)
+ )
\ No newline at end of file
diff --git a/extensions/chaeo/workflows.py b/extensions/chaeo/workflows.py
index a47986f8..14e3fd2d 100644
--- a/extensions/chaeo/workflows.py
+++ b/extensions/chaeo/workflows.py
@@ -83,6 +83,16 @@ def export_patches_from_multichannel_zstack(
)
ti.click('export_annotated_zstack')
+ # from extensions.chaeo.zmask import build_image_flattening_zmask_from_points
+ #
+ # dff = df[df['keeper'] == True]
+ # build_image_flattening_zmask_from_points(
+ # dff['centroid-0'],
+ # dff['centroid-1'],
+ # dff['zi'],
+ # stack.get_one_channel_data(patches_channel).data,
+ # )
+
return {
'pixel_model_id': px_model.model_id,
'input_filepath': input_zstack_path,
diff --git a/extensions/chaeo/zmask.py b/extensions/chaeo/zmask.py
index 66e01f95..6206c737 100644
--- a/extensions/chaeo/zmask.py
+++ b/extensions/chaeo/zmask.py
@@ -2,6 +2,8 @@ import numpy as np
import pandas as pd
from skimage.measure import find_contours, label, regionprops_table
+from sklearn.preprocessing import PolynomialFeatures
+from sklearn.linear_model import LinearRegression
from model_server.accessors import GenericImageDataAccessor
@@ -143,4 +145,50 @@ def build_zmask_from_object_mask(
'argmax': argmax,
}
- return zi_st, meta, df, interm
\ No newline at end of file
+ return zi_st, meta, df, interm
+
+
+def project_stack_from_focal_points(
+ xx: np.ndarray,
+ yy: np.ndarray,
+ zz: np.ndarray,
+ stack: GenericImageDataAccessor,
+ degree: int = 2,
+):
+ # TODO: add weights
+ """
+ Given a set of 3D points, project a multichannel z-stack
+ :param xx:
+ :param yy:
+ :param zz:
+ :param stack:
+ :param degree:
+ :return:
+ """
+ assert xx.shape == yy.shape
+ assert xx.shape == zz.shape
+ assert stack.chroma == 1
+
+ poly = PolynomialFeatures(degree=degree)
+ X = np.stack([xx, yy]).T
+ features = poly.fit_transform(X, zz)
+ model = LinearRegression(fit_intercept=False)
+ model.fit(features, zz)
+
+ output_shape = stack.hw
+ xy_indices = np.indices(output_shape).reshape(2, -1).T
+ xy_features = np.dot(
+ poly.fit_transform(xy_indices, zz),
+ model.coef_
+ )
+ zi_image = xy_features.reshape(
+ output_shape
+ ).round().clip(
+ 0, stack.nz
+ ).astype('uint16')
+
+ return np.take_along_axis(
+ stack.data[:, :, 0, :],
+ np.expand_dims(zi_image, 2),
+ axis=2
+ ).reshape(output_shape)
--
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