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towards fiducial detection

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This commit is contained in:
zamofing_t
2022-09-15 14:46:30 +02:00
parent e4b3ad0b5f
commit 7534eec921
5 changed files with 319 additions and 101 deletions
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80
geometry.py
View File

@@ -248,7 +248,7 @@ class geometry:
_log.debug('least square data:\nK:{}\nAA:{}'.format(K, AA))
@staticmethod
def autofocus(cam,mot,rng=(-1,1),n=30):
def autofocus(cam,mot,rng=(-1,1),n=30,saveImg=False):
# cam camera object
# mot motor object
# rng region (min max relative to current position) to seek
@@ -256,33 +256,11 @@ class geometry:
# roi region of interrest to calculate sharpness
# mode mode to calculate sharpness (sum/max-min/hist? of edge detection in roi)
import PIL.Image
from scipy import ndimage
v=np.ndarray(shape=(len(cam),2))
if type(cam) == list:
for i, fn in enumerate(cam):
img=PIL.Image.open(fn)
img=np.asarray(img)
s=ndimage.sobel(img)
v[i,0]=s.sum()
v[i,1]=s.std()
#fft=np.log(np.abs(np.fft.fft2(img)))
#fft=np.fft.fftshift(fft)
#s=np.array(fft.shape,dtype=np.uint16)/2
#fft[300:700,400:800]=0
#v[i,1]=fft.sum()
#if i&0x3==0:
# plt.figure()
# plt.imshow(fft)
fig, ax=plt.subplots()
mx=v.max(0)
mn=v.min(0)
v=(v-mn)/(mx-mn)
#ax.plot(v[:,0])
ax.plot(v)
plt.show()
pass
else:
if mot is not None:
p0=mot.get_rbv()
else:
p0=0
if saveImg:
for i,p in enumerate(np.linspace(p0+rng[0],p0+rng[1],n)):
mot.move_abs(p,wait=True)
pic=cam._pic# get_image()
@@ -292,11 +270,55 @@ class geometry:
pic=np.array(pic/scl, dtype=np.uint8)
elif pic.dtype!=np.uint8:
pic=np.array(pic, dtype=np.uint8)
img=PIL.Image.fromarray(pic)
fn=f'/tmp/image{i:03d}.png'
img.save(fn)
_log.debug(f'{fn} {pic.dtype} {pic.min()} {pic.max()}')
mot.move_abs(p0)
return p0
else:
from scipy import ndimage, signal
if type(cam) == list:
imgLst=cam
n=len(imgLst)
mtr=np.ndarray(shape=(n,))
posLst=np.linspace(p0+rng[0], p0+rng[1], n)
for i,p in enumerate(posLst):
if type(cam)==list:
img=PIL.Image.open(imgLst[i])
img=np.asarray(img)
else:
mot.move_abs(p, wait=True)
img=cam._pic # get_image()
img16=np.array(img, np.int16)
msk=np.array(((1, 0, -1), (2, 0, -2), (1, 0, -1)), np.int16)
sb1=signal.convolve2d(img16, msk, mode='same', boundary='fill', fillvalue=0)
sb2=signal.convolve2d(img16, msk.T, mode='same', boundary='fill', fillvalue=0)
sb=np.abs(sb1)+np.abs(sb2)
mtr[i]=sb.sum()
_log.debug(f'{i}/{p:.4g} -> {mtr[i]:.4g}')
mx=mtr.argmax()
_log.debug(f'best focus at idx:{mx}= pos:{posLst[mx]} = metric:{mtr[mx]:.6g}')
if mx>0 and mx <len(posLst):
#fit parabola and interpolate:
# y=ax2+bx+c, at positions x=-1, 0, 1, y'= 2a+b == 0 (top of parabola)
# calc a,b,c:
# y(-1)=a-b+c
# y( 0)= +c
# y( 1)=a+b+c
# c=y(0)
# b=(y(1)-y(-1))/2
# a=(y(1)+y(-1))/2-y(0)
# x=-b/2a=(y(-1)-y(1))/2(y(-1)+y(1)-2y(0))
u,v,w=mtr[mx-1:mx+2]
d=posLst[1]-posLst[0]
p=posLst[mx]+d*.5*(u-w)/(u+w-2*v)
else:
p=posLst[mx]
if mot is not None:
mot.move_abs(p)
return p
pass
def pix2pos(self, p, zoom=None):
@@ -603,7 +625,7 @@ if __name__=="__main__":
if args.mode&0x08:
import glob
imgLst=sorted(glob.glob("scratch/image*.png"))
imgLst=sorted(glob.glob("scratch/autofocus2/image*.png"))
geometry.autofocus(imgLst,None)

2
psi_device.py
View File

@@ -6,7 +6,7 @@ if hostname=='ganymede':
else:
sys.path.insert(0, os.path.expanduser('/sf/cristallina/applications/mx/zamofing_t/PBTools/'))
sys.path.insert(0, os.path.expanduser("/photonics/home/gac-cristall/Documents/swissmx_cristallina/slic/"))
from slic.core.acquisition import SFAcquisition
#from slic.core.acquisition import SFAcquisition
import logging

32
swissmx.py
View File

@@ -492,11 +492,14 @@ class WndSwissMx(QMainWindow, Ui_MainWindow):
action.triggered.connect(self._OLD_escape_goToTellMountPosition)
self.toolBar.addAction(action)
action = QAction(icon, "Auto\nFocus", self)
action.triggered.connect(self.cb_autofocus)
self.toolBar.addAction(action)
action = QAction(icon, "Test\nCode", self)
action.triggered.connect(self.cb_testcode)
self.toolBar.addAction(action)
self.toolBar.addWidget(qutilities.horiz_spacer())
icon = qtawesome.icon("material.sync")
@@ -1359,6 +1362,8 @@ class WndSwissMx(QMainWindow, Ui_MainWindow):
if pic.max()>255:
scl=2**int(round(np.log2(mx)-8))
pic=np.array(pic/scl,dtype=np.uint8)
elif pic.dtype!=np.uint8:
pic=np.array(pic, dtype=np.uint8)
except AttributeError:
sim=app._camera._sim
pic=cam._sim['imgSeq'][sim['imgIdx']]
@@ -1582,6 +1587,11 @@ Author Thierry Zamofing (thierry.zamofing@psi.ch)
QMessageBox.about(self, "SwissMX", txt)
pass
def cb_autofocus(self):
app=QApplication.instance()
geo=app._geometry
#geo.autofocus(app._camera, self.tweakers['base_z'],rng=(-1, 1), n=30,saveImg=True)
geo.autofocus(app._camera, self.tweakers['base_z'],rng=(-1, 1), n=10)
def cb_testcode(self):
try:
@@ -1598,18 +1608,13 @@ Author Thierry Zamofing (thierry.zamofing@psi.ch)
plt.stem(x, y)
plt.show(block=False)
step=2
step=5
if step==0:
vb=self.vb
vb.autoRange(items=(self._goImg,))
elif step==1:
testMatplotlib()
elif step==2:
app=QApplication.instance()
cfg=app._cfg
geo=app._geometry
geo.autofocus(app._camera, self.tweakers['base_z'])
elif step==3:
grp=pg.ItemGroup()
vb.addItem(grp)
obj=UsrGO.Marker((100, 100), (100, 100), mode=1)
@@ -1620,7 +1625,7 @@ Author Thierry Zamofing (thierry.zamofing@psi.ch)
grp.addItem(obj)
tc['grp']=grp
vb.autoRange(items=(obj,))
elif step==4:
elif step==3:
grp=tc['grp']
tr=grp.transform()
# UsrGO.obj_info(tr)
@@ -1628,7 +1633,16 @@ Author Thierry Zamofing (thierry.zamofing@psi.ch)
-.2, 1, 0,
0, 0, 1)
grp.setTransform(tr)
elif step==4:
app=QApplication.instance()
cfg=app._cfg
geo=app._geometry
geo.autofocus(app._camera, self.tweakers['base_z'],rng=(-1, 1), n=30,saveImg=True)
elif step==5:
app=QApplication.instance()
cfg=app._cfg
geo=app._geometry
geo.autofocus(app._camera, self.tweakers['base_z'],rng=(-1, 1), n=10)
#print(vb.childGroup.childItems())
pass

168
workbench/autofocus.py
View File

@@ -4,91 +4,135 @@ Demonstrate a simple data-slicing task: given 3D data (displayed at top), select
a 2D plane and interpolate data along that plane to generate a slice image
(displayed at bottom).
https://www.hindawi.com/journals/js/2021/5643054/
https://www.hindawi.com/journals/mpe/2021/8243072/
"""
## Add path to library (just for examples; you do not need this)
import logging
import numpy as np
_log=logging.getLogger(__name__)
import numpy as np
import PIL.Image
from scipy import ndimage,signal
import glob
from pyqtgraph.Qt import QtCore, QtGui
import pyqtgraph as pg
app=QtGui.QApplication([])
## Create window with two ImageView widgets
win=QtGui.QMainWindow()
win.resize(800, 800)
win.setWindowTitle('pyqtgraph example: DataSlicing')
cw=QtGui.QWidget()
win.setCentralWidget(cw)
l=QtGui.QGridLayout()
cw.setLayout(l)
imv1=pg.ImageView()
imv2=pg.ImageView()
l.addWidget(imv1, 0, 0)
l.addWidget(imv2, 1, 0)
sld=QtGui.QSlider(QtCore.Qt.Horizontal)
sld.setMinimum(10)
sld.setMaximum(30)
sld.setValue(20)
sld.setTickPosition(QtGui.QSlider.TicksBelow)
sld.setTickInterval(5)
class autofocus(QtGui.QMainWindow):
def __init__(self, parent = None):
super(autofocus, self).__init__(parent)
self.resize(800, 1500)
self.setWindowTitle('pyqtgraph example: DataSlicing')
cw=QtGui.QWidget()
self.setCentralWidget(cw)
l=QtGui.QGridLayout()
cw.setLayout(l)
l.addWidget(sld, 2, 0)
win.show()
#self._imgLst=imgLst=sorted(glob.glob("../scratch/autofocus1/image*.png"))
self._imgLst=imgLst=sorted(glob.glob("../scratch/autofocus2/image*.png"))
self._metrics=mtr=np.ndarray(shape=(len(imgLst), 5))
mtr[:]=0
self._sld=sld=QtGui.QSlider(QtCore.Qt.Horizontal)
sld.setMinimum(0)
sld.setMaximum(len(imgLst)-1)
sld.setValue(0)
sld.setTickPosition(QtGui.QSlider.TicksBelow)
sld.setTickInterval(1)
sld.valueChanged.connect(self.cb_sld_change)
roi=pg.LineSegmentROI([[10, 64], [120, 64]], pen='r')
imv1.addItem(roi)
self._imv1=imv1=pg.ImageView()
self._imv2=imv2=pg.ImageView()
x1=np.linspace(-30, 10, 128)[:, np.newaxis, np.newaxis]
x2=np.linspace(-20, 20, 128)[:, np.newaxis, np.newaxis]
y=np.linspace(-30, 10, 128)[np.newaxis, :, np.newaxis]
z=np.linspace(-20, 20, 128)[np.newaxis, np.newaxis, :]
d1=np.sqrt(x1**2+y**2+z**2)
d2=2*np.sqrt(x1[::-1]**2+y**2+z**2)
d3=4*np.sqrt(x2**2+y[:, ::-1]**2+z**2)
data=(np.sin(d1)/d1**2)+(np.sin(d2)/d2**2)+(np.sin(d3)/d3**2)
#spl=QtGui.QSplitter(QtCore.Qt.Horizontal)
self._pw=pw=pg.PlotWidget(name='Plot1') ## giving the plots names allows us to link
import PIL.Image
from scipy import ndimage
import glob
imgLst=sorted(glob.glob("image*.png"))
v=np.ndarray(shape=(len(imgLst), 2))
#for i, fn in enumerate(imgLst):
# img=PIL.Image.open(fn)
# img=np.asarray(img)
# s=ndimage.sobel(img)
# v[i, 0]=s.sum()
# v[i, 1]=s.std()
#fig, ax=plt.subplots()
#mx=v.max(0)
#mn=v.min(0)
#v=(v-mn)/(mx-mn)
# ax.plot(v[:,0])
#ax.plot(v)
#plt.show()
# pass
self._plt=plt=[]
for c in ('rgbcy'):
plt.append(pw.plot(pen=c))
def update():
global data, imv1, imv2, imgLst
d2=roi.getArrayRegion(data, imv1.imageItem, axes=(1, 2))
imv2.setImage(d2)
pw.resize(100,100)
pw.setMaximumSize(2000,200)
l.addWidget(sld, 0, 0)
l.addWidget(imv1, 1, 0)
l.addWidget(imv2, 2, 0)
l.addWidget(pw, 3, 0)
## Display the data
self.cb_sld_change(0,True)
mtr[1:,:]=mtr[0,:]
self._imv1.setHistogramRange(0, 100)
self._imv1.setLevels(0, 40)
self._imv2.setHistogramRange(0, 100)
self._imv2.setLevels(0, 40)
def cb_sld_change(self,val,auto=False):
i=self._sld.value()
_log.debug(f'{i}')
fn= self._imgLst[i]
img=PIL.Image.open(fn)
img=np.asarray(img)
#slb=ndimage.sobel(img)
img16=np.array(img,np.int16)
s1=np.array(((1,0,-1),(2,0,-2),(1,0,-1)),np.int16)
sb1=signal.convolve2d(img16, s1, mode='same', boundary='fill', fillvalue=0)
sb2=signal.convolve2d(img16, s1.T, mode='same', boundary='fill', fillvalue=0)
sb=np.abs(sb1)+np.abs(sb2)
#remove irrelevant low values
idx=sb[:]<20
sbLut=sb*1
sbLut[idx]=0
#import numpy as np
#import matplotlib.pyplot as plt
mx=sb.max()+1
lut=(np.sin(np.arange(mx)/mx*np.pi-np.pi/2)+1)*128
#lut=((np.arcsin(np.arange(mx)/(mx-1)*2-1)/np.pi)+.5)*255
#lut=np.array(lut*255,np.uint16)
#sbLut=lut[sb]
#import matplotlib.pyplot as plt
#plt.plot(lut);plt.show()
#img2=ndimage.grey_dilation(sb,size=(5,5)) #, size=None, footprint=None, structure=None, output=None, mode='reflect', cval=0.0, origin=0)
img2=ndimage.grey_closing(sb,size=(25,25)) #, size=None, footprint=None, structure=None, output=None, mode='reflect', cval=0.0, origin=0)
roi.sigRegionChanged.connect(update)
#fft=np.log(np.abs(np.fft.fft2(sb)))
#fft=np.fft.fftshift(fft)
# fft[300:700,400:800]=0
# v[i,1]=fft.sum()
## Display the data
imv1.setImage(data)
imv1.setHistogramRange(-0.01, 0.01)
imv1.setLevels(-0.003, 0.003)
self._imv1.setImage(sb,autoRange=auto,autoLevels=auto,autoHistogramRange=auto)
#self._imv2.setImage(sb,autoRange=auto,autoLevels=auto,autoHistogramRange=auto)
self._imv2.setImage(sbLut,autoRange=auto,autoLevels=auto,autoHistogramRange=auto)
mtr=self._metrics
update()
mtr[i, 0]=img.std()
mtr[i, 1]=sb.sum()
mtr[i, 2]=sb.std()
mtr[i, 3]=sbLut.sum()#sb.std()
mtr[i, 4]=sbLut.std()#img2.sum()
mx=mtr.max(0)
mn=mtr.min(0)
mtr=(mtr-mn)/(mx-mn)
_log.debug(f'{i} {mtr[i,:]}')
for i in range(mtr.shape[1]):
self._plt[i].setData(mtr[:,i])
## Start Qt event loop unless running in interactive mode.
if __name__=='__main__':
import sys
logging.basicConfig(level=logging.DEBUG, format='%(levelname)s:%(module)s:%(lineno)d:%(funcName)s:%(message)s ')
app=QtGui.QApplication([])
af=autofocus()
af.show()
if (sys.flags.interactive!=1) or not hasattr(QtCore, 'PYQT_VERSION'):
QtGui.QApplication.instance().exec_()

138
workbench/fiducialDetection.py Normal file
View File

@@ -0,0 +1,138 @@
# -*- coding: utf-8 -*-
"""
Demonstrate a simple data-slicing task: given 3D data (displayed at top), select
a 2D plane and interpolate data along that plane to generate a slice image
(displayed at bottom).
https://www.hindawi.com/journals/js/2021/5643054/
https://www.hindawi.com/journals/mpe/2021/8243072/
"""
import logging
import numpy as np
_log=logging.getLogger(__name__)
import numpy as np
import PIL.Image
from scipy import ndimage,signal
import glob
from pyqtgraph.Qt import QtCore, QtGui
import pyqtgraph as pg
class fiducial(QtGui.QMainWindow):
def __init__(self, parent = None):
super(autofocus, self).__init__(parent)
self.resize(800, 1500)
self.setWindowTitle('pyqtgraph example: DataSlicing')
cw=QtGui.QWidget()
self.setCentralWidget(cw)
l=QtGui.QGridLayout()
cw.setLayout(l)
#self._imgLst=imgLst=sorted(glob.glob("../scratch/autofocus1/image*.png"))
self._imgLst=imgLst=sorted(glob.glob("../scratch/autofocus2/image*.png"))
self._metrics=mtr=np.ndarray(shape=(len(imgLst), 5))
mtr[:]=0
self._sld=sld=QtGui.QSlider(QtCore.Qt.Horizontal)
sld.setMinimum(0)
sld.setMaximum(len(imgLst)-1)
sld.setValue(0)
sld.setTickPosition(QtGui.QSlider.TicksBelow)
sld.setTickInterval(1)
sld.valueChanged.connect(self.cb_sld_change)
self._imv1=imv1=pg.ImageView()
self._imv2=imv2=pg.ImageView()
#spl=QtGui.QSplitter(QtCore.Qt.Horizontal)
self._pw=pw=pg.PlotWidget(name='Plot1') ## giving the plots names allows us to link
self._plt=plt=[]
for c in ('rgbcy'):
plt.append(pw.plot(pen=c))
pw.resize(100,100)
pw.setMaximumSize(2000,200)
l.addWidget(sld, 0, 0)
l.addWidget(imv1, 1, 0)
l.addWidget(imv2, 2, 0)
l.addWidget(pw, 3, 0)
## Display the data
self.cb_sld_change(0,True)
mtr[1:,:]=mtr[0,:]
self._imv1.setHistogramRange(0, 100)
self._imv1.setLevels(0, 40)
self._imv2.setHistogramRange(0, 100)
self._imv2.setLevels(0, 40)
def cb_sld_change(self,val,auto=False):
i=self._sld.value()
_log.debug(f'{i}')
fn= self._imgLst[i]
img=PIL.Image.open(fn)
img=np.asarray(img)
#slb=ndimage.sobel(img)
img16=np.array(img,np.int16)
s1=np.array(((1,0,-1),(2,0,-2),(1,0,-1)),np.int16)
sb1=signal.convolve2d(img16, s1, mode='same', boundary='fill', fillvalue=0)
sb2=signal.convolve2d(img16, s1.T, mode='same', boundary='fill', fillvalue=0)
sb=np.abs(sb1)+np.abs(sb2)
#remove irrelevant low values
idx=sb[:]<20
sbLut=sb*1
sbLut[idx]=0
#import numpy as np
#import matplotlib.pyplot as plt
mx=sb.max()+1
lut=(np.sin(np.arange(mx)/mx*np.pi-np.pi/2)+1)*128
#lut=((np.arcsin(np.arange(mx)/(mx-1)*2-1)/np.pi)+.5)*255
#lut=np.array(lut*255,np.uint16)
#sbLut=lut[sb]
#import matplotlib.pyplot as plt
#plt.plot(lut);plt.show()
#img2=ndimage.grey_dilation(sb,size=(5,5)) #, size=None, footprint=None, structure=None, output=None, mode='reflect', cval=0.0, origin=0)
img2=ndimage.grey_closing(sb,size=(25,25)) #, size=None, footprint=None, structure=None, output=None, mode='reflect', cval=0.0, origin=0)
#fft=np.log(np.abs(np.fft.fft2(sb)))
#fft=np.fft.fftshift(fft)
# fft[300:700,400:800]=0
# v[i,1]=fft.sum()
self._imv1.setImage(sb,autoRange=auto,autoLevels=auto,autoHistogramRange=auto)
#self._imv2.setImage(sb,autoRange=auto,autoLevels=auto,autoHistogramRange=auto)
self._imv2.setImage(sbLut,autoRange=auto,autoLevels=auto,autoHistogramRange=auto)
mtr=self._metrics
mtr[i, 0]=img.std()
mtr[i, 1]=sb.sum()
mtr[i, 2]=sb.std()
mtr[i, 3]=sbLut.sum()#sb.std()
mtr[i, 4]=sbLut.std()#img2.sum()
mx=mtr.max(0)
mn=mtr.min(0)
mtr=(mtr-mn)/(mx-mn)
_log.debug(f'{i} {mtr[i,:]}')
for i in range(mtr.shape[1]):
self._plt[i].setData(mtr[:,i])
## Start Qt event loop unless running in interactive mode.
if __name__=='__main__':
import sys
logging.basicConfig(level=logging.DEBUG, format='%(levelname)s:%(module)s:%(lineno)d:%(funcName)s:%(message)s ')
app=QtGui.QApplication([])
fd=fiducial()
fd.show()
if (sys.flags.interactive!=1) or not hasattr(QtCore, 'PYQT_VERSION'):
QtGui.QApplication.instance().exec_()