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better but not yet perfect autofocus

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zamofing_t
2022-09-19 17:20:00 +02:00
parent 21afed9739
commit c3542ad38c
7 changed files with 223 additions and 93 deletions
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246
geometry.py
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@@ -255,84 +255,6 @@ class geometry:
_log.debug('least square data:\nK:{}\nAA:{}'.format(K, AA))
@staticmethod
def autofocus(cam,mot,rng=(-1,1),n=30,progressDlg=None,saveImg=False):
# cam camera object
# mot motor object (e.g. SimMotorTweak)
# rng region (min max relative to current position) to seek
# n number of images to take in region
# progressDlg a pg.ProgressDialog to allow to abort the function call
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()
mx=pic.max()
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)
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:
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.get_image() # get latest 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()
try:
progressDlg+=1
if progressDlg.wasCanceled():
return
except TypeError as e:
pass
_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>1 and mx+2<=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
@staticmethod
def find_fiducial(cam,sz=(210,210),brd=(20,20)):
if type(cam)==str:
@@ -340,6 +262,8 @@ class geometry:
img=np.asarray(img)
else:
img=cam.get_image() # get latest image
if img.dtype==np.uint16:
img=np.array(img,np.uint8)
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
@@ -481,6 +405,169 @@ class geometry:
self._fitPlane=aa
class autofocus:
def __init__(self,cam,mot=None):
# cam camera object or image list
# mot motor object (e.g. SimMotorTweak) or None
# rng region (min max relative to current position) to seek
self._cam=cam
self._mot=mot
def save_img(self,rng=(-1,1),n=30,progressDlg=None):
mot=self._mot
cam=self._cam
try:
p0=mot.get_rbv()
except AttributeError:
_log.warning('needs a real motor')
return
for i,p in enumerate(np.linspace(p0+rng[0],p0+rng[1],n)):
mot.move_abs(p,wait=True)
try:
pic=cam._pic
except AttributeError:
pic=cam.get_image()
mx=pic.max()
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)
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)
def cb_autofocus(self,*args,**kwargs):
cam=self._cam
mot=self._mot
mtr=self._mtr
msk=self._msk
idx=self._idx
p=mot.get_rbv()
img16=np.array(cam._pic, 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)
m=sb.sum()
mtr[idx,:]=(p,m)
_log.debug(f'{args} {kwargs} p:{p} mtr={m}')
print(p)
if abs(p-self._pDst)<0.01:
_log.debug(f'DONE->{self._idx}')
del cam.process
print(mtr[:idx,:])
mx=mtr[:,1].argmax()
self._af=self.interpolate(mtr[:idx,0], mtr[:idx,1])
return
self._idx+=1
#if p==mot.move_abs(p0+rng[1], wait=False)
# move to sharp location
# and unregister callback
def run_continous(self,rng=(-1,1),velo=0.5):
#do not stop and go, use ballback for processing
mot=self._mot
cam=self._cam
p0=mot.get_rbv()
v=mot._motor.get('VELO')
p0=mot.get_rbv()
mot._motor.put('VELO',2)
mot.move_abs(p0+rng[0], wait=True)
mot._motor.put('VELO',velo)
n=int((rng[1]-rng[0])/velo)*20 # assume max 20fps
self._mtr=mtr=np.ndarray(shape=(n,2))
self._idx=0
self._pDst=p0+rng[1]
self._msk=np.array(((1, 0, -1), (2, 0, -2), (1, 0, -1)), np.int16)
cam.process=self.cb_autofocus
mot.move_abs(p0+rng[1], wait=False)
import pyqtgraph as pg
import time
with pg.ProgressDialog('Progress', 0, n) as dlg:
while True:
try:
p=self._af
except AttributeError:
time.sleep(.1)
dlg.setValue(self._idx)
continue
break
_log.debug(f' Final AF:{p}')
mot._motor.put('VELO',2)
mot.move_abs(p, wait=False)
@staticmethod
def interpolate(posLst,mtr):
mx=mtr[:].argmax()
_log.debug(f'best focus at idx:{mx}= pos:{posLst[mx]} = metric:{mtr[mx]:.6g}')
if mx>1 and mx+2<=mtr.shape[0]:
#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]
return p
def run(self,rng=(-1,1),n=30,progressDlg=None,saveImg=False):
# rng region (min max relative to current position) to seek
# n number of images to take in region
# progressDlg a pg.ProgressDialog to allow to abort the function call
mot=self._mot
cam=self._cam
if mot is not None:
p0=mot.get_rbv()
else:
p0=0
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.get_image() # get latest 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()
try:
progressDlg+=1
if progressDlg.wasCanceled():
return
except TypeError as e:
pass
_log.debug(f'{i}/{p:.4g} -> {mtr[i]:.4g}')
p=autofocus.interpolate(posLst,mtr)
if mot is not None:
mot.move_abs(p)
return p
if __name__=="__main__":
import argparse
@@ -676,7 +763,8 @@ if __name__=="__main__":
if args.mode&0x08:
import glob
imgLst=sorted(glob.glob("scratch/autofocus2/image*.png"))
geometry.autofocus(imgLst,None)
af=autofocus(imgLst,None)
af.run()
if args.mode&0x10:
geometry.find_fiducial("scratch/fiducial/image001.png")