def CalcPartialCrossCorrFun(img1, img2, nDiv, fragCoords):
roiNR, roiNC = img1.height // nDiv, img1.width // nDiv
fragsToCorrelate1 = []
fragsToCorrelate2 = []
for x, y in fragCoords:
frag1 = imsup.CropImageROI(img1, (y * roiNR, x * roiNC),
(roiNR, roiNC), 1)
fragsToCorrelate1.append(frag1)
frag2 = imsup.CropImageROI(img2, (y * roiNR, x * roiNC),
(roiNR, roiNC), 1)
fragsToCorrelate2.append(frag2)
ccfAvg = imsup.Image(roiNR, roiNC, imsup.Image.cmp['CAP'],
imsup.Image.mem['GPU'])
for frag1, frag2 in zip(fragsToCorrelate1, fragsToCorrelate2):
ccf = CalcCrossCorrFun(frag1, frag2)
ccfAvg.amPh.am = arrsup.AddTwoArrays(ccfAvg.amPh.am, ccf.amPh.am)
return ccfAvg
def CalcCrossCorrFun(img1, img2):
fft1 = FFT(img1)
fft2 = FFT(img2)
fft1.ReIm2AmPh()
fft2.ReIm2AmPh()
fft3 = imsup.Image(fft1.height, fft1.width, imsup.Image.cmp['CAP'],
imsup.Image.mem['GPU'])
fft1.amPh = imsup.ConjugateAmPhMatrix(fft1.amPh)
fft3.amPh = imsup.MultAmPhMatrices(fft1.amPh, fft2.amPh)
fft3.amPh.am = arrsup.CalcSqrtOfArray(fft3.amPh.am) # mcf ON
# ---- ccf ----
# fft3.amPh.am = fft1.amPh.am * fft2.amPh.am
# fft3.amPh.ph = -fft1.amPh.ph + fft2.amPh.ph
# ---- mcf ----
# fft3.amPh.am = np.sqrt(fft1.amPh.am * fft2.amPh.am)
# fft3.amPh.ph = -fft1.amPh.ph + fft2.amPh.ph
ccf = IFFT(fft3)
ccf = FFT2Diff(ccf)
ccf.ReIm2AmPh()
return ccf
def CalcAverageCrossCorrFun(img1, img2, nDiv):
roiNR, roiNC = img1.height // nDiv, img1.width // nDiv
fragsToCorrelate1 = []
fragsToCorrelate2 = []
# mozna to wszystko urownoleglic (tak jak w CreateFragment())
for y in range(0, nDiv):
for x in range(0, nDiv):
frag1 = imsup.CropImageROI(img1, (y * roiNR, x * roiNC),
(roiNR, roiNC), 1)
fragsToCorrelate1.append(frag1)
frag2 = imsup.CropImageROI(img2, (y * roiNR, x * roiNC),
(roiNR, roiNC), 1)
fragsToCorrelate2.append(frag2)
ccfAvg = imsup.Image(roiNR, roiNC, imsup.Image.cmp['CAP'],
imsup.Image.mem['GPU'])
for frag1, frag2 in zip(fragsToCorrelate1, fragsToCorrelate2):
ccf = CalcCrossCorrFun(frag1, frag2)
ccfAvg.amPh.am = arrsup.AddTwoArrays(ccfAvg.amPh.am, ccf.amPh.am)
return ccfAvg
def PerformIWFR(images, N):
imgHeight, imgWidth = images[0].height, images[0].width
ewfResultsDir = 'results/ewf/'
ewfAmName = 'am'
ewfPhName = 'ph'
# backCTFunctions = []
# forwCTFunctions = []
print('Starting IWFR...')
# storing contrast transfer functions
# for img in images:
# # print(imgWidth, img.px_dim, -img.defocus)
# ctf = CalcTransferFunction(imgWidth, img.px_dim, -img.defocus)
# ctf.AmPh2ReIm()
# # ctf.reIm = ccc.Diff2FFT(ctf.reIm)
# backCTFunctions.append(ctf)
#
# ctf = CalcTransferFunction(imgWidth, img.px_dim, img.defocus)
# ctf.AmPh2ReIm()
# # ctf.reIm = ccc.Diff2FFT(ctf.reIm)
# forwCTFunctions.append(ctf)
# start IWFR procedure
exitWave = imsup.Image(imgHeight, imgWidth, imsup.Image.cmp['CRI'],
imsup.Image.mem['GPU'])
for i in range(0, N):
print('Iteration no {0}...'.format(i + 1))
imsup.ClearImageData(exitWave)
# backpropagation (to in-focus plane)
ccfg.GetGPUMemoryUsed() # !!!
for img, idx in zip(images, range(0, len(images))):
# img = PropagateWave(img, backCTFunctions[idx]) # faster, but uses more memory
img = PropagateToFocus(img) # slower, but uses less memory
img.AmPh2ReIm()
exitWave.reIm = arrsup.AddTwoArrays(exitWave.reIm, img.reIm)
exitWave.reIm = arrsup.MultArrayByScalar(exitWave.reIm,
1 / len(images))
ewfAmPath = ewfResultsDir + ewfAmName + str(i + 1) + '.png'
ewfPhPath = ewfAmPath.replace(ewfAmName, ewfPhName)
ewfAmplPhPath = ewfPhPath.replace(ewfPhName, ewfPhName + 'Ampl')
imsup.SaveAmpImage(exitWave, ewfAmPath)
imsup.SavePhaseImage(exitWave, ewfPhPath)
amplifExitPhase = FilterPhase(exitWave)
imsup.SavePhaseImage(amplifExitPhase, ewfAmplPhPath)
# forward propagation (to the original focus plane)
ccfg.GetGPUMemoryUsed() # !!!
for img, idx in zip(images, range(0, len(images))):
# images[idx] = PropagateWave(exitWave, forwCTFunctions[idx])
images[idx] = PropagateBackToDefocus(exitWave, img.defocus)
images[idx].amPh.am = img.amPh.am # restore original amplitude
print('All done')
return exitWave