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very promissing fiducial detection

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zamofing_t
2022-09-15 19:19:13 +02:00
parent 7534eec921
commit 6a7b5ab91e
4 changed files with 197 additions and 58 deletions
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55
geometry.py
View File

@@ -16,10 +16,18 @@ modes:
0x02: update_optical_center
'''
import logging
import numpy as np
_log=logging.getLogger(__name__)
import numpy as np
import PIL.Image
try:
from scipy import ndimage, signal
except ImportError as e:
_log.warning(e)
try:
import cv2 as cv
except ImportError as e:
_log.warning(e)
class geometry:
@@ -255,7 +263,6 @@ class geometry:
# n number of images to take in region
# roi region of interrest to calculate sharpness
# mode mode to calculate sharpness (sum/max-min/hist? of edge detection in roi)
import PIL.Image
if mot is not None:
p0=mot.get_rbv()
else:
@@ -277,7 +284,6 @@ class geometry:
mot.move_abs(p0)
return p0
else:
from scipy import ndimage, signal
if type(cam) == list:
imgLst=cam
n=len(imgLst)
@@ -321,6 +327,45 @@ class geometry:
return p
pass
@staticmethod
def find_fiducial(cam,sz=(210,210),brd=(20,20)):
if type(cam)==str:
img=PIL.Image.open(cam)
img=np.asarray(img)
else:
img=cam._pic # get_image()
img16=np.array(img, np.int16)
fid=np.ones((sz[1]+2*brd[1],sz[0]+2*brd[0]),dtype=np.uint8)*255
fid[brd[1]:sz[1]+brd[1],brd[0]:sz[0]+brd[0]]=0
mask=np.ones((sz[1]+2*brd[1],sz[0]+2*brd[0]),dtype=np.uint8)*255
mask[2*brd[1]:sz[1],2*brd[0]:sz[0]]=0
#https://docs.opencv.org/4.5.2/d4/dc6/tutorial_py_template_matching.html
#res = cv.matchTemplate(img,fid,cv.TM_CCORR_NORMED )
res = cv.matchTemplate(img,fid,cv.TM_CCORR_NORMED,mask=mask)
h,w=img.shape
fh2,fw2=fid.shape
fw2//=2
fh2//=2
mtr=np.ndarray((5,2),np.uint16)
corr=np.ndarray((5,),np.float32)
for i in range(5):
p=np.unravel_index(res.argmax(), res.shape)
corr[i]=res[p]
mtr[i,:]=p
y0=max(p[0]-fh2,0)
y1=min(p[0]+fh2,h)
x0=max(p[1]-fw2,0)
x1=min(p[1]+fw2,w)
res[y0:y1,x0:x1]*=.5
pos=mtr.mean(0)[::-1]+(fw2,fh2)
crm=corr.mean()
_log.debug(f'position: {pos} correlation:{crm}')
return (pos,crm)
def pix2pos(self, p, zoom=None):
# returns the position m(x,y) in meter relative to the optical center at a given zoom level of the pixel p(x,y)
# if zoom=None, the last zoom value is used
@@ -627,6 +672,8 @@ if __name__=="__main__":
import glob
imgLst=sorted(glob.glob("scratch/autofocus2/image*.png"))
geometry.autofocus(imgLst,None)
if args.mode&0x10:
geometry.find_fiducial("scratch/fiducial/image001.png")
# pix2pos="[[1.0, 200.0, 400.0, 600.0, 800.0], [[[0.001182928623952055, -2.6941995127711305e-05], [-4.043716694634124e-05, -0.0011894314084263825]], [[0.0007955995220142541, -3.175003727901119e-05], [-2.0896601103372113e-05, -0.0008100805094631365]], [[0.00048302539335378367, -1.1661121407652543e-05], [-2.0673746995751222e-05, -0.0004950857899461772]], [[0.00028775903460576395, -1.3762555219494508e-05], [-9.319936861519268e-06, -0.0002889214488565999]], [[0.0001788819256630411, -6.470841493681516e-06], [-2.0336605088889967e-06, -0.0001831131753499113]]]]"

13
pyqtUsrObj.py
View File

@@ -527,6 +527,17 @@ class FixTargetFrame(pg.ROI):
## Start Qt event loop unless running in interactive mode or using pyside.
if __name__=='__main__':
def set_fiducial(pic):
# fiducial test
f=np.array(((0, 0, 0, 0, 0),
(0, 1, 1, 1, 0),
(0, 1, 0, 0, 0),
(0, 1, 1, 0, 0),
(0, 1, 0, 0, 0),
(0, 0, 0, 0, 0),), pic.dtype)
pic[0:6, 0:5]=f*pic.max()
# TODO: pg.ItemGroup does not support bounding box and therefore vb.autoRange() does not work
class ItemGroup(pg.ItemGroup):
# own item group that supports bounding rect
@@ -667,7 +678,7 @@ if __name__=='__main__':
arr[:, 50]=10
arr+=np.sin(np.linspace(0, 20, 100)).reshape(1, 100)
arr+=np.random.normal(size=(100, 100))
set_fiducial(arr)
# add an arrow for asymmetry
arr[10, :50]=10
arr[9:12, 44:48]=10

25
swissmx.py
View File

@@ -496,6 +496,10 @@ class WndSwissMx(QMainWindow, Ui_MainWindow):
action.triggered.connect(self.cb_autofocus)
self.toolBar.addAction(action)
action = QAction(icon, "Find\nFiducial", self)
action.triggered.connect(self.cb_find_fiducial)
self.toolBar.addAction(action)
action = QAction(icon, "Test\nCode", self)
action.triggered.connect(self.cb_testcode)
self.toolBar.addAction(action)
@@ -1593,7 +1597,17 @@ Author Thierry Zamofing (thierry.zamofing@psi.ch)
#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_find_fiducial(self):
app=QApplication.instance()
geo=app._geometry
#geo.autofocus(app._camera, self.tweakers['base_z'],rng=(-1, 1), n=30,saveImg=True)
pos,corr=geo.find_fiducial(app._camera, sz=(210,210),brd=(20,20))
pass
def cb_testcode(self):
app=QApplication.instance()
cfg=app._cfg
geo=app._geometry
try:
tc=self._testCode
tc['idx']+=1
@@ -1608,13 +1622,14 @@ Author Thierry Zamofing (thierry.zamofing@psi.ch)
plt.stem(x, y)
plt.show(block=False)
step=5
step=6
if step==0:
vb=self.vb
vb.autoRange(items=(self._goImg,))
elif step==1:
testMatplotlib()
elif step==2:
vb=self.vb
grp=pg.ItemGroup()
vb.addItem(grp)
obj=UsrGO.Marker((100, 100), (100, 100), mode=1)
@@ -1634,15 +1649,11 @@ Author Thierry Zamofing (thierry.zamofing@psi.ch)
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)
elif step==6:
geo.find_fiducial(app._camera)
#print(vb.childGroup.childItems())
pass

162
workbench/fiducialDetection.py
View File

@@ -14,17 +14,50 @@ import numpy as np
_log=logging.getLogger(__name__)
import numpy as np
import cv2 as cv
import PIL.Image
from scipy import ndimage,signal
import glob
import glob, os
from pyqtgraph.Qt import QtCore, QtGui
import pyqtgraph as pg
pg.setConfigOptions(imageAxisOrder='row-major')
def set_fiducial(pic):
# fiducial test
f=np.array(((0, 0, 0, 0, 0),
(0, 1, 1, 1, 0),
(0, 1, 0, 0, 0),
(0, 1, 1, 0, 0),
(0, 1, 0, 0, 0),
(0, 0, 0, 0, 0),), pic.dtype)
pic[0:6, 0:5]=f*pic.max()
def wtestimages():
fn=os.path.expanduser('~/Documents/prj/SwissFEL/epics_ioc_modules/ESB_MX/python/SwissMX/scratch/fiducial/image{idx:03d}.png')
img=np.kron(np.array([[1, 0] * 5, [0, 1] * 5] * 6,dtype=np.uint8), np.ones((100, 100),dtype=np.uint8)*255)
set_fiducial(img)
pil_img=PIL.Image.fromarray(img)
pil_img.save(fn.format(idx=2))
img=np.ndarray((1000,1200),dtype=np.uint8)
img[:]=255
#img=np.zeros((1200,1000),dtype=np.uint8)
fid=np.array([[0, 1] * 2, [1, 0] * 2] * 2,dtype=np.uint8)[:3,:3]
fid=np.kron(fid, np.ones((210, 210),dtype=np.uint8)*255)
img[100:100+fid.shape[0],200:200+fid.shape[1]]=fid
set_fiducial(img)
pil_img=PIL.Image.fromarray(img)
pil_img.save(fn.format(idx=3))
img=np.ndarray((1200,1000))
wtestimages()
class fiducial(QtGui.QMainWindow):
def __init__(self, parent = None):
super(autofocus, self).__init__(parent)
super(fiducial, self).__init__(parent)
self.resize(800, 1500)
self.setWindowTitle('pyqtgraph example: DataSlicing')
cw=QtGui.QWidget()
@@ -33,7 +66,7 @@ class fiducial(QtGui.QMainWindow):
cw.setLayout(l)
#self._imgLst=imgLst=sorted(glob.glob("../scratch/autofocus1/image*.png"))
self._imgLst=imgLst=sorted(glob.glob("../scratch/autofocus2/image*.png"))
self._imgLst=imgLst=sorted(glob.glob("../scratch/fiducial/*.png"))
self._metrics=mtr=np.ndarray(shape=(len(imgLst), 5))
mtr[:]=0
self._sld=sld=QtGui.QSlider(QtCore.Qt.Horizontal)
@@ -69,8 +102,10 @@ class fiducial(QtGui.QMainWindow):
self._imv1.setHistogramRange(0, 100)
self._imv1.setLevels(0, 40)
self._imv2.setHistogramRange(0, 100)
self._imv2.setLevels(0, 40)
#self._imv2.setHistogramRange(0, 100)
#self._imv2.setLevels(0, 40)
self._imv2.setHistogramRange(0, 1)
self._imv2.setLevels(0, 1)
def cb_sld_change(self,val,auto=False):
i=self._sld.value()
@@ -78,53 +113,88 @@ class fiducial(QtGui.QMainWindow):
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)
#pil_img=PIL.Image.fromarray(img)
#pil_img.save('../scratch/fiducial/image002.png')
#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)
#fn='/home/zamofing_t/Documents/prj/SwissFEL/epics_ioc_modules/ESB_MX/python/SwissMX/scratch/fiducial/zoom0400.png'
#pil_img=PIL.Image.open(fn+'_')
#img=np.asarray(pil_img)
#img=np.array(img,dtype=np.uint8)
#pil_img=PIL.Image.fromarray(img)
#pil_img.save(fn)
#fft=np.log(np.abs(np.fft.fft2(sb)))
#img16=np.array(img,np.int16)
#fft=np.log(np.abs(np.fft.fft2(img)))
#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
fid=np.array([[0, 1]*2, [1, 0]*2]*2, dtype=np.uint8)[:3, :3]
fid=np.kron(fid, np.ones((100, 100), dtype=np.uint8)*255)
#res = cv.matchTemplate(img,fid,cv.TM_CCORR_NORMED )
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()
#fid=np.ones((250,250),dtype=np.uint8)*255
#fid[20:230,20:230]=0
mx=mtr.max(0)
mn=mtr.min(0)
mtr=(mtr-mn)/(mx-mn)
sz=(90, 90); brd=(20, 20) # zoom 001
#sz=(130, 130); brd=(20, 20) # zoom 200
#sz=(210, 210); brd=(20, 20) # zoom 400
fid=np.ones((sz[1]+2*brd[1],sz[0]+2*brd[0]),dtype=np.uint8)*255
fid[brd[1]:sz[1]+brd[1],brd[0]:sz[0]+brd[0]]=0
mask=np.ones((sz[1]+2*brd[1],sz[0]+2*brd[0]),dtype=np.uint8)*255
mask[2*brd[1]:sz[1],2*brd[0]:sz[0]]=0
_log.debug(f'{i} {mtr[i,:]}')
for i in range(mtr.shape[1]):
self._plt[i].setData(mtr[:,i])
#https://docs.opencv.org/4.5.2/d4/dc6/tutorial_py_template_matching.html
#res = cv.matchTemplate(img,fid,cv.TM_CCORR_NORMED )
res = cv.matchTemplate(img,fid,cv.TM_CCORR_NORMED,mask=mask)
corr_u8=np.array(res*255,np.uint8)
h,w=img.shape
fh2,fw2=fid.shape
fw2//=2
fh2//=2
mtr=np.ndarray((5,2),np.uint16)
corr=np.ndarray((5,),np.float32)
for i in range(5):
p=np.unravel_index(res.argmax(), res.shape)
corr[i]=res[p]
mtr[i,:]=p
y0=max(p[0]-fh2,0)
y1=min(p[0]+fh2,h)
x0=max(p[1]-fw2,0)
x1=min(p[1]+fw2,w)
res[y0:y1,x0:x1]*=.5
res[p[0],p[1]]=0
corr_u8=np.array(res*255,np.uint8)
ctr=mtr.mean(0,dtype=np.int32)+(fw2,fh2)
try:
img=img*1
img[ctr[0]-5:ctr[0]+5,ctr[1]-5:ctr[1]+5]=255
img[ctr[0],:]=0
img[:,ctr[1]]=0
except IndexError as e:
pass
self._imv1.setImage(img,autoRange=auto,autoLevels=auto,autoHistogramRange=auto)
self._imv2.setImage(res,autoRange=auto,autoLevels=auto,autoHistogramRange=auto)
pos=mtr.mean(0)[::-1]+(fw2,fh2)
_log.debug(f'position: {pos} correlation:{corr.mean()}')
#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__':