diff --git a/src/napari_segment/_widget.py b/src/napari_segment/_widget.py
index d70195064e324fabe81d4f8e84b5d771be67a0a9..aeb08ba61242665aea3c09944d50102b78e66a9a 100644
--- a/src/napari_segment/_widget.py
+++ b/src/napari_segment/_widget.py
@@ -6,18 +6,27 @@ see: https://napari.org/plugins/stable/guides.html#widgets
Replace code below according to your needs.
"""
-from enum import Enum
+import logging
import os
-from functools import partial
-from tempfile import TemporaryFile
+from enum import Enum
+from functools import partial, reduce
+from importlib.metadata import PackageNotFoundError, version
import dask
import magicgui.widgets as w
import napari
import numpy as np
+import pandas as pd
import qtpy.QtWidgets as q
import yaml
from magicgui import magic_factory
+from matplotlib.backends.backend_qt5agg import (
+ FigureCanvasQTAgg as FigureCanvas,
+)
+from matplotlib.backends.backend_qt5agg import (
+ NavigationToolbar2QT as NavigationToolbar,
+)
+from matplotlib.figure import Figure
from napari.layers import Image
from napari.utils.notifications import show_error, show_info
from scipy.ndimage import (
@@ -26,17 +35,8 @@ from scipy.ndimage import (
gaussian_filter,
label,
)
-from functools import reduce
from skimage.measure import regionprops
-
-from matplotlib.backends.backend_qt5agg import (FigureCanvasQTAgg as FigureCanvas)
-from matplotlib.backends.backend_qt5agg import NavigationToolbar2QT as NavigationToolbar
-from matplotlib.figure import Figure
-import matplotlib
-from threading import Thread
-import logging
-from importlib.metadata import PackageNotFoundError, version
-import pandas as pd
+from skimage.segmentation import clear_border
try:
__version__ = version("napari-segment")
@@ -64,10 +64,9 @@ class SegmentStack(q.QWidget):
# 2. use a type annotation of 'napari.viewer.Viewer' for any parameter
class Choices(Enum):
- INT="Invert"
- GRAD="Gradient"
- GDIF="Gauss diff"
-
+ INT = "Invert"
+ GRAD = "Gradient"
+ GDIF = "Gauss diff"
def __init__(self, napari_viewer):
super().__init__()
@@ -90,7 +89,9 @@ class SegmentStack(q.QWidget):
orientation="horizontal",
)
- self.thr = w.FloatSlider(label="Threshold", min=0.1, max=0.9, value=.4)
+ self.thr = w.FloatSlider(
+ label="Threshold", min=0.1, max=0.9, value=0.4
+ )
self.erode = w.SpinBox(label="erode", min=0, max=10, value=0)
@@ -99,7 +100,7 @@ class SegmentStack(q.QWidget):
choices=[v.value for v in self.Choices],
value=self.Choices.INT.value,
orientation="horizontal",
- allow_multiple=True
+ allow_multiple=True,
)
self.smooth = w.SpinBox(label="smooth", min=0, max=10, value=2)
@@ -115,19 +116,30 @@ class SegmentStack(q.QWidget):
)
self.max_ecc = w.FloatSlider(
- label="Max eccentricity",
- min=0.0,
- max=1.0,
- value=.9
+ label="Max eccentricity", min=0.0, max=1.0, value=0.9
)
- self.btn = q.QPushButton("Save params!")
+ self.btn_save_params = q.QPushButton("Save params!")
self.btn_save_csv = q.QPushButton("Save csv!")
self.check_auto_plot = w.CheckBox(label="Update Plots")
self.check_auto_plot.changed.connect(self.plot_stats)
- self.canvas = FigureCanvas(Figure(figsize=(5,5)))
+ self.pixel_size = 1
+ self.pixel_unit = "px"
+ self.pixel_size_widget = w.LineEdit(
+ label="Pixel size",
+ value=self.pixel_size,
+ ) # bind=self.set_pixel_size)
+ self.pixel_unit_widget = w.LineEdit(
+ label="unit", value=self.pixel_unit
+ ) # , bind=self.set_pixel_unit)
+ self.pixel_block = w.Container(
+ widgets=[self.pixel_size_widget, self.pixel_unit_widget],
+ layout="horizontal",
+ )
+
+ self.canvas = FigureCanvas(Figure(figsize=(5, 5)))
self.ax = self.canvas.figure.subplots(nrows=3, sharex=False)
self.ax[0].set_title("Number of detections")
self.ax[1].set_title(diams_title := "Diameters")
@@ -135,9 +147,15 @@ class SegmentStack(q.QWidget):
self.ax[2].set_title("Eccentricities")
self.canvas.figure.tight_layout()
- self._count, = self.ax[0].plot(range(10), [0]*10, "o", picker=True, pickradius=5)
- self._diams, = self.ax[1].plot(range(10), [0]*10, "o", picker=True, pickradius=5)
- self._eccs, = self.ax[2].plot(range(10), [0]*10, "o", picker=True, pickradius=5)
+ (self._count,) = self.ax[0].plot(
+ range(10), [0] * 10, "o", picker=True, pickradius=5
+ )
+ (self._diams,) = self.ax[1].plot(
+ range(10), [0] * 10, "o", picker=True, pickradius=5
+ )
+ (self._eccs,) = self.ax[2].plot(
+ range(10), [0] * 10, "o", picker=True, pickradius=5
+ )
self.container = w.Container(
label="Container",
@@ -154,13 +172,14 @@ class SegmentStack(q.QWidget):
self.min_diam,
self.max_diam,
self.max_ecc,
- self.check_auto_plot
- ]
+ ],
)
self.setLayout(q.QVBoxLayout())
self.layout().addWidget(self.container.native)
- self.layout().addWidget(self.btn)
+ self.layout().addWidget(self.btn_save_params)
+ self.layout().addWidget(self.check_auto_plot.native)
+ self.layout().addWidget(self.pixel_block.native)
self.layout().addWidget(self.canvas)
self.layout().addWidget(NavigationToolbar(self.canvas, self))
self.layout().addWidget(self.btn_save_csv)
@@ -172,8 +191,8 @@ class SegmentStack(q.QWidget):
self.input.changed.connect(self.restore_params)
self.input.changed.connect(self.preprocess)
- self.canvas.mpl_connect('button_press_event', self.onfigclick)
- self.canvas.mpl_connect('pick_event', self.on_pick)
+ self.canvas.mpl_connect("button_press_event", self.onfigclick)
+ self.canvas.mpl_connect("pick_event", self.on_pick)
logger.debug("Initialization finished.")
@@ -187,18 +206,25 @@ class SegmentStack(q.QWidget):
new_[0] = slice
self.viewer.dims.current_step = tuple(new_)
-
def onfigclick(self, event):
- print('%s click: button=%d, x=%d, y=%d, xdata=%f, ydata=%f' %
- ('double' if event.dblclick else 'single', event.button,
- event.x, event.y, event.xdata, event.ydata))
+ print(
+ "%s click: button=%d, x=%d, y=%d, xdata=%f, ydata=%f"
+ % (
+ "double" if event.dblclick else "single",
+ event.button,
+ event.x,
+ event.y,
+ event.xdata,
+ event.ydata,
+ )
+ )
self.move_step(np.round(event.xdata, 0).astype(int))
def on_pick(self, event):
line = event.artist
xdata, ydata = line.get_data()
ind = event.ind
- print(f'on pick line: {np.array([xdata[ind], ydata[ind]]).T}')
+ print(f"on pick line: {np.array([xdata[ind], ydata[ind]]).T}")
self.move_step(xdata[ind])
@@ -209,16 +235,23 @@ class SegmentStack(q.QWidget):
return get_gradient(data2D, smooth=self.smooth.value)
def _gdif(self, data2D):
- return (
- gaussian_filter(data2D, self.smooth.value)
- - gaussian_filter(data2D, self.smooth.value + 2)
+ return gaussian_filter(data2D, self.smooth.value) - gaussian_filter(
+ data2D, self.smooth.value + 2
)
+ def set_pixel_size(self, value):
+ self.pixel_size = value
+ self.pixel_size_widget.value = value
+
+ def set_pixel_unit(self, unit):
+ self.pixel_unit = unit
+ self.pixel_unit_widget.value = unit
+
def preprocess(self):
if not self.input.current_choice:
return
logger.debug(f"start preprocessing {self.input.current_choice}")
-
+
try:
self.path = self.viewer.layers[self.input.current_choice].metadata[
"path"
@@ -235,23 +268,24 @@ class SegmentStack(q.QWidget):
except KeyError:
return
-
+
try:
- self.pixel_size = self.viewer.layers[self.input.current_choice]\
- .metadata["pixel_size_um"]
- self.unit = "um"
+ pixel_size = self.viewer.layers[
+ self.input.current_choice
+ ].metadata["pixel_size_um"]
+ unit = "um"
+ self.set_pixel_size(pixel_size)
+ self.set_pixel_unit(unit)
except KeyError:
self.pixel_size = 1
- self.unit = "px"
-
- logger.debug(f"pixel size: {self.pixel_size} {self.unit}")
+ self.pixel_unit = "px"
+
+ logger.debug(f"pixel size: {self.pixel_size} {self.pixel_unit}")
- self.ax[1].set_title(f"{self.diams_title}, {self.unit}")
-
self.scale = np.ones((len(self.data.shape),))
self.scale[-2:] = self.binning
- logger.debug(f'Computed scale for napari {self.scale}')
+ logger.debug(f"Computed scale for napari {self.scale}")
if isinstance(self.data, np.ndarray):
chunksize = np.ones(len(self.data.shape))
@@ -261,10 +295,10 @@ class SegmentStack(q.QWidget):
)
else:
self.ddata = self.data.astype("f")
-
- logger.debug(f'Dask array: {self.ddata}')
- logger.debug(f'Processing data with {self.use.value}')
+ logger.debug(f"Dask array: {self.ddata}")
+
+ logger.debug(f"Processing data with {self.use.value}")
# show_info(self.use.value)
if self.use.value == self.Choices.GRAD.value:
self.smooth_gradient = self.ddata.map_blocks(
@@ -283,8 +317,10 @@ class SegmentStack(q.QWidget):
)
else:
self.smooth_gradient = np.zeros_like(self.ddata)
- logger.error(f"""Filter `{self.use.value}` not understood!
- Expected {[v.value for v in self.Choices]}""")
+ logger.error(
+ f"""Filter `{self.use.value}` not understood!
+ Expected {[v.value for v in self.Choices]}"""
+ )
raise (
ValueError(
f"""Filter `{self.use.value}` not understood!
@@ -293,27 +329,33 @@ class SegmentStack(q.QWidget):
)
if not (name := "Preprocessing") in self.viewer.layers:
- logger.debug(f'No Preprocessing layer found, adding one')
+ logger.debug("No Preprocessing layer found, adding one")
self.viewer.add_image(
data=self.smooth_gradient,
**{"name": name, "scale": self.scale},
)
else:
- logger.debug(f'Updating Preprocessing layer with \
- {self.smooth_gradient}')
+ logger.debug(
+ f"Updating Preprocessing layer with \
+ {self.smooth_gradient}"
+ )
self.viewer.layers[name].data = self.smooth_gradient
self.viewer.layers[name].scale = self.scale
-
- logger.debug(f'Preprocessing finished, \
- sending {self.smooth_gradient} to thresholding')
+
+ logger.debug(
+ f"Preprocessing finished, \
+ sending {self.smooth_gradient} to thresholding"
+ )
self.threshold()
def threshold(self):
- logger.debug('Start thresholding step')
+ logger.debug("Start thresholding step")
if not self.input.current_choice:
return
- logger.debug(f'Thresholding with the thr={self.thr.value} \
- and erode={self.erode.value}')
+ logger.debug(
+ f"Thresholding with the thr={self.thr.value} \
+ and erode={self.erode.value}"
+ )
self.labels = self.smooth_gradient.map_blocks(
partial(
threshold_gradient, thr=self.thr.value, erode=self.erode.value
@@ -321,7 +363,7 @@ class SegmentStack(q.QWidget):
dtype=np.int32,
)
if not (name := "Detections") in self.viewer.layers:
- logger.debug(f'No Detections layer found, adding one')
+ logger.debug("No Detections layer found, adding one")
self.viewer.add_labels(
data=self.labels,
opacity=0.3,
@@ -329,27 +371,30 @@ class SegmentStack(q.QWidget):
)
else:
- logger.debug(f'Updating Detections layer with {self.labels}')
+ logger.debug(f"Updating Detections layer with {self.labels}")
self.viewer.layers[name].data = self.labels
self.viewer.layers[name].scale = self.scale
-
+
self.viewer.layers[name].contour = 8 // self.binning
-
-
- logger.debug(f'Thresholding succesful. \
- Sending labels {self.labels} to filtering')
+
+ logger.debug(
+ f"Thresholding succesful. \
+ Sending labels {self.labels} to filtering"
+ )
self.update_out()
def update_out(self):
if not self.input.current_choice:
return
- logger.debug(f'Start filtering')
+ logger.debug("Start filtering")
try:
- logger.debug(f"""Filtering labels by \
+ logger.debug(
+ f"""Filtering labels by \
({self.min_diam.value / self.binning} \
< size[px] < {self.max_diam.value / self.binning}) \
- and eccentricity > {self.max_ecc.value}""")
+ and eccentricity > {self.max_ecc.value}"""
+ )
selected_labels = dask.array.map_blocks(
filter_labels,
@@ -361,9 +406,8 @@ class SegmentStack(q.QWidget):
)
self.selected_labels = selected_labels
-
if not (name := "selected labels") in self.viewer.layers:
- logger.debug(f'No selected labels layer found, adding one')
+ logger.debug("No selected labels layer found, adding one")
self.viewer.add_labels(
data=selected_labels,
@@ -371,13 +415,12 @@ class SegmentStack(q.QWidget):
**{"name": name, "scale": self.scale},
)
else:
- logger.debug(f'Updating labels layer with {selected_labels}')
+ logger.debug(f"Updating labels layer with {selected_labels}")
self.viewer.layers[name].scale = self.scale
self.viewer.layers[name].data = selected_labels
# self.save_params()
-
except TypeError as e:
show_error(f"Relax filter! {e}")
@@ -386,50 +429,54 @@ class SegmentStack(q.QWidget):
except Exception as e:
show_error(f"Plot failed: {e}")
-
def plot_stats(self, ignore_check_auto_plot=False):
if not self.check_auto_plot.value:
if not ignore_check_auto_plot:
return
- props = [regionprops(label_image=img) for img in self.selected_labels.compute()]
- num_regions_per_frame = [len(p) for p in props]
+ self.pixel_size = float(self.pixel_size_widget.value)
+ self.pixel_unit = str(self.pixel_unit_widget.value)
+ self.ax[1].set_title(f"{self.diams_title}, {self.pixel_unit}")
+
+ props = [
+ regionprops(label_image=img)
+ for img in self.selected_labels.compute()
+ ]
+ num_regions_per_frame = [len(p) for p in props]
area_ = [
[
- (i, prop.area * (self.binning * self.pixel_size)**2) \
+ (i, prop.area * (self.binning * self.pixel_size) ** 2)
for prop in props_per_frame
- ] for i,props_per_frame in enumerate(props)
- ]
- area = reduce(lambda a,b: a+b, area_[:])
-
- self.props_df = \
- pd.DataFrame(
- data=area,
- columns=["frame", (area_col := f"area [{self.unit}$^2$]")]
- )
- self.props_df.loc[:, (diam_col := f"diameter [{self.unit}]")] = \
+ ]
+ for i, props_per_frame in enumerate(props)
+ ]
+ area = reduce(lambda a, b: a + b, area_[:])
+
+ self.props_df = pd.DataFrame(
+ data=area,
+ columns=["frame", (area_col := f"area [{self.pixel_unit}$^2$]")],
+ )
+ self.props_df.loc[:, (diam_col := f"diameter [{self.pixel_unit}]")] = (
np.sqrt(self.props_df[area_col]) * 2 / np.pi
+ )
eccs_ = [
- [
- (prop.eccentricity) for prop in props_per_frame
- ] for i,props_per_frame in enumerate(props)
- ]
- eccs = reduce(lambda a,b: a+b, eccs_)
+ [(prop.eccentricity) for prop in props_per_frame]
+ for i, props_per_frame in enumerate(props)
+ ]
+ eccs = reduce(lambda a, b: a + b, eccs_)
self.props_df.loc[:, (ecc_col := "eccentricity")] = eccs
-
- data=self.props_df
+ data = self.props_df
self._count.set_data(*zip(*enumerate(num_regions_per_frame)))
self._diams.set_data(data["frame"], data[diam_col])
self._eccs.set_data(data["frame"], data[ecc_col])
[a.set_xlim(0, len(num_regions_per_frame)) for a in self.ax]
self.ax[0].set_ylim(0, max(num_regions_per_frame) + 1)
self.ax[1].set_ylim(
- self.props_df[diam_col].min(),
- self.props_df[diam_col].max()
+ self.props_df[diam_col].min(), self.props_df[diam_col].max()
)
- self.ax[2].set_ylim(0,1)
+ self.ax[2].set_ylim(0, 1)
self.canvas.draw_idle()
@@ -442,6 +489,8 @@ class SegmentStack(q.QWidget):
show_error(f"Unable to find the data to save: {e}")
return
path = self.path + ".table.csv"
+ self.props_df.loc[:, "filename"] = os.path.basename(self.path)
+ self.props_df.loc[:, "layer"] = self.input.current_choice
try:
self.props_df.to_csv(path)
logger.info(f"Saved csv {path}")
@@ -450,8 +499,6 @@ class SegmentStack(q.QWidget):
logger.error(f"Error saving csv: {e}")
show_error(f"Error saving csv: {e}")
-
-
def save_params(self):
data = {
"binning": self.binning,
@@ -462,9 +509,11 @@ class SegmentStack(q.QWidget):
"min_diameter": self.min_diam.value,
"max_diameter": self.max_diam.value,
"max_ecc": self.max_ecc.value,
+ "pixel_size": self.pixel_size,
+ "pixel_unit": self.pixel_unit,
}
try:
-
+
dir = os.path.dirname(self.path)
filename = os.path.basename(self.path)
new_name = filename + ".params.yaml"
@@ -481,7 +530,7 @@ class SegmentStack(q.QWidget):
logger.info(f"Parameters saves into {ff}")
def restore_params(self):
- logger.debug(f'Start restoring parameters')
+ logger.debug("Start restoring parameters")
try:
self.path = self.viewer.layers[self.input.current_choice].metadata[
"path"
@@ -509,7 +558,7 @@ class SegmentStack(q.QWidget):
show_info(f"restoring parameters from {ppp}")
except FileNotFoundError:
return
- logger.debug(f'Loaded parameters: {data}')
+ logger.debug(f"Loaded parameters: {data}")
try:
self.binning_widget.value = data["binning"]
self.use.value = data["use"]
@@ -519,10 +568,12 @@ class SegmentStack(q.QWidget):
self.min_diam.value = data["min_diameter"]
self.max_diam.value = data["max_diameter"]
self.max_ecc.value = data["max_ecc"]
+ self.pixel_size = data["pixel_size"]
+ self.pixel_unit = data["pixel_unit"]
except Exception as e:
show_error(f"Restore settings failed, {e}")
logger.error(f"Restore settings failed, {e}")
-
+
self.binning_widget.changed.connect(self.preprocess)
self.thr.changed.connect(self.threshold)
self.erode.changed.connect(self.threshold)
@@ -531,10 +582,9 @@ class SegmentStack(q.QWidget):
self.min_diam.changed.connect(self.update_out)
self.max_diam.changed.connect(self.update_out)
self.max_ecc.changed.connect(self.update_out)
- self.btn.clicked.connect(self.save_params)
+ self.btn_save_params.clicked.connect(self.save_params)
self.btn_save_csv.clicked.connect(self.save_csv)
-
def reset_choices(self, event=None):
logger.debug(f"New layer added. Reset choices. Event: {event}")
new_layers = [
@@ -544,12 +594,18 @@ class SegmentStack(q.QWidget):
]
if self.input.choices != new_layers:
self.input.choices = new_layers
- logger.debug(f'Updating layer list with {new_layers}')
+ logger.debug(f"Updating layer list with {new_layers}")
else:
- logger.debug('No new data layers, probably added pipeline layers triggered this reset')
+ logger.debug(
+ "No new data layers, probably added pipeline \
+ layers triggered this reset"
+ )
+
def norm01(data):
d = data.copy()
+ if d.max() == 0:
+ return d
return (a := d - d.min()) / a.max()
@@ -707,6 +763,8 @@ def threshold_gradient(
data = strip_dimensions(smoothed_gradient)
regions = data > thr * data.max()
+ regions = clear_border(regions)
+
if fill:
regions = binary_fill_holes(regions)