From 1af591200248727678b2507b364892b809428b24 Mon Sep 17 00:00:00 2001
From: Christopher Rhodes <christopher.rhodes@embl.de>
Date: Wed, 7 Feb 2024 15:51:35 +0100
Subject: [PATCH] Rearranged methods, condensed into roiset package
---
model_server/base/process.py | 15 +-
model_server/extensions/chaeo/accessors.py | 32 +++
model_server/extensions/chaeo/products.py | 247 -----------------
.../extensions/chaeo/{zmask.py => roiset.py} | 251 ++++++++++++++++--
.../extensions/chaeo/tests/test_zstack.py | 42 ++-
model_server/extensions/chaeo/workflows.py | 4 +-
6 files changed, 293 insertions(+), 298 deletions(-)
rename model_server/extensions/chaeo/{zmask.py => roiset.py} (53%)
diff --git a/model_server/base/process.py b/model_server/base/process.py
index 48128223..3ee227d7 100644
--- a/model_server/base/process.py
+++ b/model_server/base/process.py
@@ -71,4 +71,17 @@ def rescale(nda, clip=0.0):
clip_pct = (100.0 * clip, 100.0 * (1.0 - clip))
cmin, cmax = np.percentile(nda, clip_pct)
rescaled = rescale_intensity(nda, in_range=(cmin, cmax))
- return rescaled
\ No newline at end of file
+ return rescaled
+
+
+def make_rgb(nda):
+ """
+ Convert a YXCZ stack array to RGB, and error if more than three channels
+ :param nda: np.ndarray (YXCZ dimensions)
+ :return: np.ndarray of 3-channel stack
+ """
+ h, w, c, nz = nda.shape
+ assert c <= 3
+ outdata = np.zeros((h, w, 3, nz), dtype=nda.dtype)
+ outdata[:, :, 0:c, :] = nda[:, :, :, :]
+ return outdata
diff --git a/model_server/extensions/chaeo/accessors.py b/model_server/extensions/chaeo/accessors.py
index bc65c6f3..1f1278a3 100644
--- a/model_server/extensions/chaeo/accessors.py
+++ b/model_server/extensions/chaeo/accessors.py
@@ -1,7 +1,10 @@
from pathlib import Path
import numpy as np
+from skimage.io import imsave
+from tifffile import imwrite
+from base.process import make_rgb
from model_server.base.accessors import generate_file_accessor, InMemoryDataAccessor
class MonoPatchStack(InMemoryDataAccessor):
@@ -127,6 +130,33 @@ class Multichannel3dPatchStack(InMemoryDataAccessor):
def shape_dict(self):
return dict(zip(('P', 'Y', 'X', 'C', 'Z'), self.data.shape))
+
+def write_patch_to_file(where, fname, yxcz):
+ ext = fname.split('.')[-1].upper()
+ where.mkdir(parents=True, exist_ok=True)
+
+ if ext == 'PNG':
+ assert yxcz.dtype == 'uint8', f'Invalid data type {yxcz.dtype}'
+ assert yxcz.shape[2] <= 3, f'Cannot export images with more than 3 channels as PNGs'
+ assert yxcz.shape[3] == 1, f'Cannot export z-stacks as PNGs'
+ if yxcz.shape[2] == 1:
+ outdata = yxcz[:, :, 0, 0]
+ elif yxcz.shape[2] == 2: # add a blank blue channel
+ outdata = make_rgb(yxcz)
+ else: # preserve RGB order
+ outdata = yxcz[:, :, :, 0]
+ imsave(where / fname, outdata, check_contrast=False)
+ return True
+
+ elif ext in ['TIF', 'TIFF']:
+ zcyx = np.moveaxis(yxcz, [3, 2, 0, 1], [0, 1, 2, 3])
+ imwrite(where / fname, zcyx, imagej=True)
+ return True
+
+ else:
+ raise Exception(f'Unsupported file extension: {ext}')
+
+
class Error(Exception):
pass
@@ -135,3 +165,5 @@ class InvalidDataForPatchStackError(Error):
class FileNotFoundError(Error):
pass
+
+
diff --git a/model_server/extensions/chaeo/products.py b/model_server/extensions/chaeo/products.py
index 484756fa..b28b04f6 100644
--- a/model_server/extensions/chaeo/products.py
+++ b/model_server/extensions/chaeo/products.py
@@ -1,250 +1,3 @@
-from math import floor, sqrt
-from pathlib import Path
-import numpy as np
-import pandas as pd
-from scipy.stats import moment
-from skimage.filters import sobel
-from skimage.io import imsave
-from skimage.measure import find_contours, shannon_entropy
-from tifffile import imwrite
-from model_server.extensions.chaeo.accessors import MonoPatchStack
-from model_server.extensions.chaeo.annotators import draw_box_on_patch, draw_contours_on_patch
-from model_server.base.accessors import InMemoryDataAccessor
-from model_server.base.process import pad, rescale, resample_to_8bit
-def _make_rgb(zs):
- h, w, c, nz = zs.shape
- assert c <= 3
- outdata = np.zeros((h, w, 3, nz), dtype=zs.dtype)
- outdata[:, :, 0:c, :] = zs[:, :, :, :]
- return outdata
-
-def _focus_metrics():
- return {
- 'max_intensity': lambda x: np.max(x),
- 'stdev': lambda x: np.std(x),
- 'max_sobel': lambda x: np.max(sobel(x)),
- 'rms_sobel': lambda x: sqrt(np.mean(sobel(x) ** 2)),
- 'entropy': lambda x: shannon_entropy(x),
- 'moment': lambda x: moment(x.flatten(), moment=2),
- }
-
-def _safe_add(a, g, b):
- assert a.dtype == b.dtype
- assert a.shape == b.shape
- assert g >= 0.0
-
- return np.clip(
- a.astype('uint32') + g * b.astype('uint32'),
- 0,
- np.iinfo(a.dtype).max
- ).astype(a.dtype)
-
-def write_patch_to_file(where, fname, yxcz):
- ext = fname.split('.')[-1].upper()
- where.mkdir(parents=True, exist_ok=True)
-
- if ext == 'PNG':
- assert yxcz.dtype == 'uint8', f'Invalid data type {yxcz.dtype}'
- assert yxcz.shape[2] <= 3, f'Cannot export images with more than 3 channels as PNGs'
- assert yxcz.shape[3] == 1, f'Cannot export z-stacks as PNGs'
- if yxcz.shape[2] == 1:
- outdata = yxcz[:, :, 0, 0]
- elif yxcz.shape[2] == 2: # add a blank blue channel
- outdata = _make_rgb(yxcz)
- else: # preserve RGB order
- outdata = yxcz[:, :, :, 0]
- imsave(where / fname, outdata, check_contrast=False)
- return True
-
- elif ext in ['TIF', 'TIFF']:
- zcyx = np.moveaxis(yxcz, [3, 2, 0, 1], [0, 1, 2, 3])
- imwrite(where / fname, zcyx, imagej=True)
- return True
-
- else:
- raise Exception(f'Unsupported file extension: {ext}')
-
-
-
-def get_patch_masks(roiset, pad_to: int = 256) -> MonoPatchStack:
- patches = []
- for roi in roiset:
- patch = np.zeros((roi.ebb_h, roi.ebb_w, 1, 1), dtype='uint8')
- patch[roi.relative_slice][:, :, 0, 0] = roi.mask * 255
-
- if pad_to:
- patch = pad(patch, pad_to)
-
- patches.append(patch)
- return MonoPatchStack(patches)
-
-
-def export_patch_masks(roiset, where: Path, pad_to: int = 256, prefix='mask', **kwargs) -> list:
- patches_acc = get_patch_masks(roiset, pad_to=pad_to)
-
- exported = []
- for i, roi in enumerate(roiset): # assumes index of patches_acc is same as dataframe
- patch = patches_acc.iat_yxcz(i)
- ext = 'png'
- fname = f'{prefix}-la{roi.label:04d}-zi{roi.zi:04d}.{ext}'
- write_patch_to_file(where, fname, patch)
- exported.append(fname)
- return exported
-
-
-def get_roiset_patches(
- roiset,
- rescale_clip: float = 0.0,
- pad_to: int = 256,
- make_3d: bool = False,
- focus_metric: str = None,
- rgb_overlay_channels: list = None,
- rgb_overlay_weights: list = [1.0, 1.0, 1.0],
- white_channel: int = None,
- **kwargs
-) -> pd.DataFrame:
-
- # arrange RGB channels if so specified, otherwise copy roiset.raw_acc data
- raw = roiset.acc_raw
- if isinstance(rgb_overlay_channels, (list, tuple)) and isinstance(rgb_overlay_weights, (list, tuple)):
- assert all([c < raw.chroma for c in rgb_overlay_channels if c is not None])
- assert len(rgb_overlay_channels) == 3
- assert len(rgb_overlay_weights) == 3
-
- if white_channel:
- assert white_channel < raw.chroma
- stack = raw.data[:, :, [white_channel, white_channel, white_channel], :]
- else:
- stack = np.zeros([*raw.shape[0:2], 3, raw.shape[3]], dtype=raw.dtype)
-
- for ii, ci in enumerate(rgb_overlay_channels):
- if ci is None:
- continue
- assert isinstance(ci, int)
- assert ci < raw.chroma
- stack[:, :, ii, :] = _safe_add(
- stack[:, :, ii, :], # either black or grayscale channel
- rgb_overlay_weights[ii],
- raw.data[:, :, ci, :]
- )
- else:
- if white_channel: # interpret as just a single channel
- assert white_channel < raw.chroma
- annotate_rgb = False
- for k in ['contour_channel', 'bounding_box_channel', 'mask_channel']:
- ca = kwargs.get(k)
- if ca is None:
- continue
- assert(ca < raw.chroma)
- if ca != white_channel:
- annotate_rgb = True
- break
- if annotate_rgb: # make RGB patches anyway to include annotation color
- stack = raw.data[:, :, [white_channel, white_channel, white_channel], :]
- else: # make monochrome patches
- stack = raw.data[:, :, [white_channel], :]
- else:
- stack = raw.data
-
- def _make_patch(roi):
- patch3d = stack[roi.slice]
- ph, pw, pc, pz = patch3d.shape
- subpatch = patch3d[roi.relative_slice]
-
- # make a 3d patch
- if make_3d:
- patch = patch3d
-
- # make a 2d patch, find optimal z-position determined by focus_metric function on each channel separately
- elif focus_metric is not None:
- foc = _focus_metrics()[focus_metric]
-
- patch = np.zeros([ph, pw, pc, 1], dtype=patch3d.dtype)
-
- for ci in range(0, pc):
- me = [foc(subpatch[:, :, ci, zi]) for zi in range(0, pz)]
- zif = np.argmax(me)
- patch[:, :, ci, 0] = patch3d[:, :, ci, zif]
-
- # make a 2d patch from middle of z-stack
- else:
- zim = floor(pz / 2)
- patch = patch3d[:, :, :, [zim]]
-
- assert len(patch.shape) == 4
-
- if rescale_clip is not None:
- patch = rescale(patch, rescale_clip)
-
- if kwargs.get('draw_bounding_box') is True:
- bci = kwargs.get('bounding_box_channel', 0)
- assert bci < 3
- if bci > 0:
- patch = _make_rgb(patch)
- for zi in range(0, patch.shape[3]):
- patch[:, :, bci, zi] = draw_box_on_patch(
- patch[:, :, bci, zi],
- ((roi.rel_x0, roi.rel_y0), (roi.rel_x1, roi.rel_y1)),
- linewidth=kwargs.get('bounding_box_linewidth', 1)
- )
-
- if kwargs.get('draw_mask'):
- mci = kwargs.get('mask_channel', 0)
- mask = np.zeros(patch.shape[0:2], dtype=bool)
- mask[roi.relative_slice[0:2]] = roi.mask
- for zi in range(0, patch.shape[3]):
- patch[:, :, mci, zi] = np.invert(mask) * patch[:, :, mci, zi]
-
- if kwargs.get('draw_contour'):
- mci = kwargs.get('contour_channel', 0)
- mask = np.zeros(patch.shape[0:2], dtype=bool)
- mask[roi.relative_slice[0:2]] = roi.mask
-
- for zi in range(0, patch.shape[3]):
- patch[:, :, mci, zi] = draw_contours_on_patch(
- patch[:, :, mci, zi],
- find_contours(mask)
- )
-
- if pad_to:
- patch = pad(patch, pad_to)
- return patch
-
- dfe = roiset.get_df()
- dfe['patch'] = roiset.get_df().apply(lambda r: _make_patch(r), axis=1)
- return dfe
-
-
-def export_patches_from_zstack(
- where: Path,
- roiset,
- prefix='patch',
- **kwargs
-):
- make_3d = kwargs.get('make_3d', False)
- patches_df = get_roiset_patches(roiset, **kwargs)
-
- def _export_patch(roi):
- patch = InMemoryDataAccessor(roi.patch)
- ext = 'tif' if make_3d or patch.chroma > 3 else 'png'
- fname = f'{prefix}-la{roi.label:04d}-zi{roi.zi:04d}.{ext}'
-
- if patch.dtype is np.dtype('uint16'):
- write_patch_to_file(where, fname, resample_to_8bit(patch.data))
- else:
- write_patch_to_file(where, fname, patch)
-
- exported.append({
- 'df_index': roi.Index,
- 'patch_filename': fname,
- 'location': where.__str__(),
- })
-
- exported = []
- for roi in patches_df.itertuples(): # just used for label info
- _export_patch(roi)
-
- return exported
\ No newline at end of file
diff --git a/model_server/extensions/chaeo/zmask.py b/model_server/extensions/chaeo/roiset.py
similarity index 53%
rename from model_server/extensions/chaeo/zmask.py
rename to model_server/extensions/chaeo/roiset.py
index 7bb1d99c..c478ff25 100644
--- a/model_server/extensions/chaeo/zmask.py
+++ b/model_server/extensions/chaeo/roiset.py
@@ -1,34 +1,68 @@
+from math import sqrt, floor
+from pathlib import Path
from uuid import uuid4
import numpy as np
import pandas as pd
+from scipy.stats import moment
+from skimage.filters import sobel
-from skimage.measure import label, regionprops_table
+from skimage.measure import label, regionprops_table, shannon_entropy, find_contours
from sklearn.preprocessing import PolynomialFeatures
from sklearn.linear_model import LinearRegression
from model_server.base.accessors import GenericImageDataAccessor, InMemoryDataAccessor, write_accessor_data_to_file
from model_server.base.models import InstanceSegmentationModel
-
-from model_server.extensions.chaeo.annotators import draw_boxes_on_3d_image
-from model_server.extensions.chaeo.products import export_patches_from_zstack
-from extensions.chaeo.params import RoiFilter, RoiSetMetaParams, RoiSetExportParams
-from model_server.extensions.chaeo.accessors import MonoPatchStack, Multichannel3dPatchStack
+from model_server.base.process import pad, rescale, resample_to_8bit, make_rgb
+from model_server.extensions.chaeo.annotators import draw_box_on_patch, draw_contours_on_patch, draw_boxes_on_3d_image
+from model_server.extensions.chaeo.params import RoiFilter, RoiSetMetaParams, RoiSetExportParams
+from model_server.extensions.chaeo.accessors import write_patch_to_file, MonoPatchStack, Multichannel3dPatchStack
from model_server.extensions.chaeo.process import mask_largest_object
-from model_server.extensions.chaeo.products import get_roiset_patches, get_patch_masks, export_patch_masks
-def get_label_ids(acc_seg_mask: GenericImageDataAccessor) -> InMemoryDataAccessor:
+def _get_label_ids(acc_seg_mask: GenericImageDataAccessor) -> InMemoryDataAccessor:
return InMemoryDataAccessor(label(acc_seg_mask.data[:, :, 0, 0]).astype('uint16'))
+
+def _focus_metrics():
+ return {
+ 'max_intensity': lambda x: np.max(x),
+ 'stdev': lambda x: np.std(x),
+ 'max_sobel': lambda x: np.max(sobel(x)),
+ 'rms_sobel': lambda x: sqrt(np.mean(sobel(x) ** 2)),
+ 'entropy': lambda x: shannon_entropy(x),
+ 'moment': lambda x: moment(x.flatten(), moment=2),
+ }
+
+
+def _safe_add(a, g, b):
+ assert a.dtype == b.dtype
+ assert a.shape == b.shape
+ assert g >= 0.0
+
+ return np.clip(
+ a.astype('uint32') + g * b.astype('uint32'),
+ 0,
+ np.iinfo(a.dtype).max
+ ).astype(a.dtype)
+
+
class RoiSet(object):
def __init__(
self,
- acc_obj_ids: GenericImageDataAccessor,
acc_raw: GenericImageDataAccessor,
+ acc_obj_ids: GenericImageDataAccessor,
params: RoiSetMetaParams = RoiSetMetaParams(),
):
+ """
+ A set of regions of interest, referenced by their positions and contours in the YXCZ space of stack acc_raw.
+ RoiSet contains their internal state, which may be exported as patches, maps, and other products by export methods.
+ :param acc_raw: accessor to a generally a multichannel z-stack
+ :param acc_obj_ids: accessor to a 2D single-channel object identities map, where each pixel's intensity
+ labels its membership in a connected object
+ :param params: optional arguments that influence the definition and representation of ROIs
+ """
assert acc_obj_ids.chroma == 1
assert acc_obj_ids.nz == 1
self.acc_obj_ids = acc_obj_ids
@@ -147,17 +181,11 @@ class RoiSet(object):
projected = self.acc_raw.data.max(axis=-1)
return projected
- def get_patch_masks(self, **kwargs):
- return get_patch_masks(self, **kwargs)
-
- def export_patch_masks(self, where, **kwargs) -> list:
- return export_patch_masks(self, where, **kwargs)
-
def get_raw_patches(self, channel=None, pad_to=256, make_3d=False): # padded, un-annotated 2d patches
if channel:
- patches_df = get_roiset_patches(self, white_channel=channel, pad_to=pad_to)
+ patches_df = self.get_patches(white_channel=channel, pad_to=pad_to)
else:
- patches_df = get_roiset_patches(self, pad_to=pad_to)
+ patches_df = self.get_patches(pad_to=pad_to)
patches = list(patches_df['patch'])
if channel is not None or self.acc_raw.chroma == 1:
return MonoPatchStack(patches)
@@ -229,6 +257,179 @@ class RoiSet(object):
om[self.acc_obj_ids.data == roi.label] = oc
self.object_class_maps[name] = InMemoryDataAccessor(om)
+ def export_patch_masks(self, where: Path, pad_to: int = 256, prefix='mask', **kwargs) -> list:
+ patches_acc = self.get_patch_masks(pad_to=pad_to)
+
+ exported = []
+ for i, roi in enumerate(self): # assumes index of patches_acc is same as dataframe
+ patch = patches_acc.iat_yxcz(i)
+ ext = 'png'
+ fname = f'{prefix}-la{roi.label:04d}-zi{roi.zi:04d}.{ext}'
+ write_patch_to_file(where, fname, patch)
+ exported.append(fname)
+ return exported
+
+
+ def export_patches(self, where: Path, prefix='patch', **kwargs):
+ make_3d = kwargs.get('make_3d', False)
+ patches_df = self.get_patches(**kwargs)
+
+ def _export_patch(roi):
+ patch = InMemoryDataAccessor(roi.patch)
+ ext = 'tif' if make_3d or patch.chroma > 3 else 'png'
+ fname = f'{prefix}-la{roi.label:04d}-zi{roi.zi:04d}.{ext}'
+
+ if patch.dtype is np.dtype('uint16'):
+ write_patch_to_file(where, fname, resample_to_8bit(patch.data))
+ else:
+ write_patch_to_file(where, fname, patch)
+
+ exported.append({
+ 'df_index': roi.Index,
+ 'patch_filename': fname,
+ 'location': where.__str__(),
+ })
+
+ exported = []
+ for roi in patches_df.itertuples(): # just used for label info
+ _export_patch(roi)
+
+ return exported
+
+ def get_patch_masks(self, pad_to: int = 256) -> MonoPatchStack:
+ patches = []
+ for roi in self:
+ patch = np.zeros((roi.ebb_h, roi.ebb_w, 1, 1), dtype='uint8')
+ patch[roi.relative_slice][:, :, 0, 0] = roi.mask * 255
+
+ if pad_to:
+ patch = pad(patch, pad_to)
+
+ patches.append(patch)
+ return MonoPatchStack(patches)
+
+ def get_patches(
+ self,
+ rescale_clip: float = 0.0,
+ pad_to: int = 256,
+ make_3d: bool = False,
+ focus_metric: str = None,
+ rgb_overlay_channels: list = None,
+ rgb_overlay_weights: list = [1.0, 1.0, 1.0],
+ white_channel: int = None,
+ **kwargs
+ ) -> pd.DataFrame:
+
+ # arrange RGB channels if so specified, otherwise copy roiset.raw_acc data
+ raw = self.acc_raw
+ if isinstance(rgb_overlay_channels, (list, tuple)) and isinstance(rgb_overlay_weights, (list, tuple)):
+ assert all([c < raw.chroma for c in rgb_overlay_channels if c is not None])
+ assert len(rgb_overlay_channels) == 3
+ assert len(rgb_overlay_weights) == 3
+
+ if white_channel:
+ assert white_channel < raw.chroma
+ stack = raw.data[:, :, [white_channel, white_channel, white_channel], :]
+ else:
+ stack = np.zeros([*raw.shape[0:2], 3, raw.shape[3]], dtype=raw.dtype)
+
+ for ii, ci in enumerate(rgb_overlay_channels):
+ if ci is None:
+ continue
+ assert isinstance(ci, int)
+ assert ci < raw.chroma
+ stack[:, :, ii, :] = _safe_add(
+ stack[:, :, ii, :], # either black or grayscale channel
+ rgb_overlay_weights[ii],
+ raw.data[:, :, ci, :]
+ )
+ else:
+ if white_channel: # interpret as just a single channel
+ assert white_channel < raw.chroma
+ annotate_rgb = False
+ for k in ['contour_channel', 'bounding_box_channel', 'mask_channel']:
+ ca = kwargs.get(k)
+ if ca is None:
+ continue
+ assert (ca < raw.chroma)
+ if ca != white_channel:
+ annotate_rgb = True
+ break
+ if annotate_rgb: # make RGB patches anyway to include annotation color
+ stack = raw.data[:, :, [white_channel, white_channel, white_channel], :]
+ else: # make monochrome patches
+ stack = raw.data[:, :, [white_channel], :]
+ else:
+ stack = raw.data
+
+ def _make_patch(roi):
+ patch3d = stack[roi.slice]
+ ph, pw, pc, pz = patch3d.shape
+ subpatch = patch3d[roi.relative_slice]
+
+ # make a 3d patch
+ if make_3d:
+ patch = patch3d
+
+ # make a 2d patch, find optimal z-position determined by focus_metric function on each channel separately
+ elif focus_metric is not None:
+ foc = _focus_metrics()[focus_metric]
+
+ patch = np.zeros([ph, pw, pc, 1], dtype=patch3d.dtype)
+
+ for ci in range(0, pc):
+ me = [foc(subpatch[:, :, ci, zi]) for zi in range(0, pz)]
+ zif = np.argmax(me)
+ patch[:, :, ci, 0] = patch3d[:, :, ci, zif]
+
+ # make a 2d patch from middle of z-stack
+ else:
+ zim = floor(pz / 2)
+ patch = patch3d[:, :, :, [zim]]
+
+ assert len(patch.shape) == 4
+
+ if rescale_clip is not None:
+ patch = rescale(patch, rescale_clip)
+
+ if kwargs.get('draw_bounding_box') is True:
+ bci = kwargs.get('bounding_box_channel', 0)
+ assert bci < 3
+ if bci > 0:
+ patch = make_rgb(patch)
+ for zi in range(0, patch.shape[3]):
+ patch[:, :, bci, zi] = draw_box_on_patch(
+ patch[:, :, bci, zi],
+ ((roi.rel_x0, roi.rel_y0), (roi.rel_x1, roi.rel_y1)),
+ linewidth=kwargs.get('bounding_box_linewidth', 1)
+ )
+
+ if kwargs.get('draw_mask'):
+ mci = kwargs.get('mask_channel', 0)
+ mask = np.zeros(patch.shape[0:2], dtype=bool)
+ mask[roi.relative_slice[0:2]] = roi.mask
+ for zi in range(0, patch.shape[3]):
+ patch[:, :, mci, zi] = np.invert(mask) * patch[:, :, mci, zi]
+
+ if kwargs.get('draw_contour'):
+ mci = kwargs.get('contour_channel', 0)
+ mask = np.zeros(patch.shape[0:2], dtype=bool)
+ mask[roi.relative_slice[0:2]] = roi.mask
+
+ for zi in range(0, patch.shape[3]):
+ patch[:, :, mci, zi] = draw_contours_on_patch(
+ patch[:, :, mci, zi],
+ find_contours(mask)
+ )
+
+ if pad_to:
+ patch = pad(patch, pad_to)
+ return patch
+
+ dfe = self._df
+ dfe['patch'] = self._df.apply(lambda r: _make_patch(r), axis=1)
+ return dfe
+
def run_exports(self, where, channel, prefix, params: RoiSetExportParams):
if not self.count:
return
@@ -240,17 +441,17 @@ class RoiSet(object):
if kp is None:
continue
if k == 'patches_3d':
- files = export_patches_from_zstack(
- subdir, self, white_channel=channel, prefix=pr, make_3d=True, **kp
+ files = self.export_patches(
+ subdir, white_channel=channel, prefix=pr, make_3d=True, **kp
)
if k == 'annotated_patches_2d':
- files = export_patches_from_zstack(
- subdir, self, prefix=pr, make_3d=False, white_channel=channel,
+ files = self.export_patches(
+ subdir, prefix=pr, make_3d=False, white_channel=channel,
bounding_box_channel=1, bounding_box_linewidth=2, **kp,
)
if k == 'patches_2d':
- files = export_patches_from_zstack(
- subdir, self, white_channel=channel, prefix=pr, make_3d=False, **kp
+ files = self.export_patches(
+ subdir, white_channel=channel, prefix=pr, make_3d=False, **kp
)
df_patches = pd.DataFrame(files)
self._df = pd.merge(self._df, df_patches, left_index=True, right_on='df_index').drop(columns='df_index')
@@ -313,3 +514,7 @@ def project_stack_from_focal_points(
),
axis=3
)
+
+
+
+
diff --git a/model_server/extensions/chaeo/tests/test_zstack.py b/model_server/extensions/chaeo/tests/test_zstack.py
index 9631dd04..f3b82997 100644
--- a/model_server/extensions/chaeo/tests/test_zstack.py
+++ b/model_server/extensions/chaeo/tests/test_zstack.py
@@ -7,9 +7,8 @@ from model_server.conf.testing import output_path
from model_server.extensions.chaeo.conf.testing import multichannel_zstack, pixel_classifier, pipeline_params
from extensions.chaeo.params import RoiSetExportParams, RoiSetMetaParams
-from model_server.extensions.chaeo.products import export_patches_from_zstack
from model_server.extensions.chaeo.workflows import infer_object_map_from_zstack
-from model_server.extensions.chaeo.zmask import get_label_ids, RoiSet
+from model_server.extensions.chaeo.roiset import _get_label_ids, RoiSet
from model_server.base.accessors import generate_file_accessor, InMemoryDataAccessor, write_accessor_data_to_file
from model_server.extensions.ilastik.models import IlastikPixelClassifierModel
from model_server.base.models import DummyInstanceSegmentationModel
@@ -42,10 +41,10 @@ class BaseTestRoiSetMonoProducts(object):
class TestRoiSetMonoProducts(BaseTestRoiSetMonoProducts, unittest.TestCase):
def _make_roi_set(self, mask_type='boxes', **kwargs):
- id_map = get_label_ids(self.seg_mask)
+ id_map = _get_label_ids(self.seg_mask)
roiset = RoiSet(
- id_map,
self.stack_ch_pa,
+ id_map,
params=RoiSetMetaParams(
mask_type=mask_type,
filters=kwargs.get('filters', {'area': {'min': 1e3, 'max': 1e4}}),
@@ -78,9 +77,9 @@ class TestRoiSetMonoProducts(BaseTestRoiSetMonoProducts, unittest.TestCase):
def test_roiset_from_non_zstacks(self, **kwargs):
acc_zstack_slice = InMemoryDataAccessor(self.stack_ch_pa.data[:, :, :, 0])
self.assertEqual(acc_zstack_slice.nz, 1)
- id_map = get_label_ids(self.seg_mask)
+ id_map = _get_label_ids(self.seg_mask)
- roiset = RoiSet(id_map, acc_zstack_slice, params=RoiSetMetaParams(mask_type='boxes'))
+ roiset = RoiSet(acc_zstack_slice, id_map, params=RoiSetMetaParams(mask_type='boxes'))
zmask = roiset.get_zmask()
zmask_acc = InMemoryDataAccessor(zmask)
@@ -105,18 +104,16 @@ class TestRoiSetMonoProducts(BaseTestRoiSetMonoProducts, unittest.TestCase):
def test_make_2d_patches(self):
roiset = self._make_roi_set()
- files = export_patches_from_zstack(
+ files = roiset.export_patches(
output_path / '2d_patches',
- roiset,
draw_bounding_box=True,
)
self.assertGreaterEqual(len(files), 1)
def test_make_3d_patches(self):
roiset = self._make_roi_set()
- files = export_patches_from_zstack(
+ files = roiset.export_patches(
output_path / '3d_patches',
- roiset,
make_3d=True)
self.assertGreaterEqual(len(files), 1)
@@ -129,12 +126,12 @@ class TestRoiSetMonoProducts(BaseTestRoiSetMonoProducts, unittest.TestCase):
self.assertEqual(result.shape, roiset.acc_raw.shape)
def test_flatten_image(self):
- id_map = get_label_ids(self.seg_mask)
+ id_map = _get_label_ids(self.seg_mask)
- roiset = RoiSet(id_map, self.stack_ch_pa, params=RoiSetMetaParams(mask_type='boxes'))
+ roiset = RoiSet(self.stack_ch_pa, id_map, params=RoiSetMetaParams(mask_type='boxes'))
df = roiset.get_df()
- from model_server.extensions.chaeo.zmask import project_stack_from_focal_points
+ from model_server.extensions.chaeo.roiset import project_stack_from_focal_points
img = project_stack_from_focal_points(
df['centroid-0'].to_numpy(),
@@ -227,10 +224,10 @@ class TestRoiSetMultichannelProducts(BaseTestRoiSetMonoProducts, unittest.TestCa
def setUp(self) -> None:
super().setUp()
- id_map = get_label_ids(self.seg_mask)
+ id_map = _get_label_ids(self.seg_mask)
self.roiset = RoiSet(
- id_map,
self.stack,
+ id_map,
params=RoiSetMetaParams(
expand_box_by=(128, 2),
mask_type='boxes',
@@ -239,9 +236,8 @@ class TestRoiSetMultichannelProducts(BaseTestRoiSetMonoProducts, unittest.TestCa
)
def test_multichannel_to_mono_2d_patches(self):
- files = export_patches_from_zstack(
+ files = self.roiset.export_patches(
output_path / 'multichannel' / 'mono_2d_patches',
- self.roiset,
white_channel=3,
draw_bounding_box=True,
)
@@ -249,9 +245,8 @@ class TestRoiSetMultichannelProducts(BaseTestRoiSetMonoProducts, unittest.TestCa
self.assertEqual(result.chroma, 1)
def test_multichannnel_to_mono_2d_patches_rgb_bbox(self):
- files = export_patches_from_zstack(
+ files = self.roiset.export_patches(
output_path / 'multichannel' / 'mono_2d_patches_rgb_bbox',
- self.roiset,
white_channel=3,
draw_bounding_box=True,
bounding_box_channel=1,
@@ -260,9 +255,8 @@ class TestRoiSetMultichannelProducts(BaseTestRoiSetMonoProducts, unittest.TestCa
self.assertEqual(result.chroma, 3)
def test_multichannnel_to_rgb_2d_patches_bbox(self):
- files = export_patches_from_zstack(
+ files = self.roiset.export_patches(
output_path / 'multichannel' / 'rgb_2d_patches_bbox',
- self.roiset,
white_channel=4,
rgb_overlay_channels=(3, None, None),
draw_mask=True,
@@ -273,9 +267,8 @@ class TestRoiSetMultichannelProducts(BaseTestRoiSetMonoProducts, unittest.TestCa
self.assertEqual(result.chroma, 3)
def test_multichannnel_to_rgb_2d_patches_contour(self):
- files = export_patches_from_zstack(
+ files = self.roiset.export_patches(
output_path / 'multichannel' / 'rgb_2d_patches_contour',
- self.roiset,
rgb_overlay_channels=(3, None, None),
draw_contour=True,
contour_channel=1,
@@ -286,9 +279,8 @@ class TestRoiSetMultichannelProducts(BaseTestRoiSetMonoProducts, unittest.TestCa
self.assertEqual(result.get_one_channel_data(2).data.max(), 0) # blue channel is black
def test_multichannel_to_multichannel_tif_patches(self):
- files = export_patches_from_zstack(
+ files = self.roiset.export_patches(
output_path / 'multichannel' / 'multichannel_tif_patches',
- self.roiset,
)
result = generate_file_accessor(Path(files[0]['location']) / files[0]['patch_filename'])
self.assertEqual(result.chroma, 5)
diff --git a/model_server/extensions/chaeo/workflows.py b/model_server/extensions/chaeo/workflows.py
index 7e90436b..08d06adf 100644
--- a/model_server/extensions/chaeo/workflows.py
+++ b/model_server/extensions/chaeo/workflows.py
@@ -10,7 +10,7 @@ from sklearn.model_selection import train_test_split
from extensions.chaeo.params import RoiSetExportParams, RoiSetMetaParams
from model_server.extensions.chaeo.process import mask_largest_object
-from model_server.extensions.chaeo.zmask import get_label_ids, RoiSet
+from model_server.extensions.chaeo.roiset import _get_label_ids, RoiSet
from model_server.base.accessors import generate_file_accessor, InMemoryDataAccessor, write_accessor_data_to_file
from model_server.base.models import Model, InstanceSegmentationModel, SemanticSegmentationModel
@@ -48,7 +48,7 @@ def infer_object_map_from_zstack(
ti.click('classify_pixels')
# make zmask
- rois = RoiSet(get_label_ids(mip_mask), stack, params=roi_params)
+ rois = RoiSet(stack, _get_label_ids(mip_mask), params=roi_params)
ti.click('generate_zmasks')
rois.classify_by(
--
GitLab