def main(self):
# load previously calculated calibration and aligned data
self.cfg.load_cal_data()
if self._lfp_img_align is None:
self.load_pickle_file()
self.load_lfp_metadata()
# micro image crop
lfp_obj = LfpCropper(lfp_img_align=self._lfp_img_align, cfg=self.cfg, sta=self.sta)
lfp_obj.main()
self._lfp_img_align = lfp_obj.lfp_img_align
del lfp_obj
# rearrange light-field to sub-aperture images
if self.cfg.params[self.cfg.opt_view]:
lfp_obj = LfpRearranger(self._lfp_img_align, cfg=self.cfg, sta=self.sta)
lfp_obj.main()
self.vp_img_linear = lfp_obj.vp_img_arr
del lfp_obj
# remove outliers if option is set
if self.cfg.params[self.cfg.opt_lier]:
obj = LfpOutliers(vp_img_arr=self.vp_img_linear, cfg=self.cfg, sta=self.sta)
obj.main()
self.vp_img_linear = obj.vp_img_arr
del obj
# color equalization
if self.cfg.params[self.cfg.opt_colo]:
obj = LfpColorEqualizer(vp_img_arr=self.vp_img_linear, cfg=self.cfg, sta=self.sta)
obj.main()
self.vp_img_linear = obj.vp_img_arr
del obj
# copy light-field for refocusing process prior to contrast alignment and export
self.vp_img_arr = self.vp_img_linear.copy() if self.vp_img_linear is not None else None
# color management automation
obj = LfpContrast(vp_img_arr=self.vp_img_arr, cfg=self.cfg, sta=self.sta)
obj.main()
self.vp_img_arr = obj.vp_img_arr
del obj
# reduction of hexagonal sampling artifacts
if self.cfg.params[self.cfg.opt_arti]:
obj = HexCorrector(vp_img_arr=self.vp_img_arr, cfg=self.cfg, sta=self.sta)
obj.main()
self.vp_img_arr = obj.vp_img_arr
del obj
# write viewpoint data to hard drive
if self.cfg.params[self.cfg.opt_view]:
obj = LfpExporter(vp_img_arr=self.vp_img_arr, cfg=self.cfg, sta=self.sta)
obj.write_viewpoint_data()
del obj
return True
def main(self):
# rearrange light-field to viewpoint representation
self.viewpoint_extraction()
# histogram equalization
if self.cfg.params[self.cfg.opt_cont]:
obj = HistogramEqualizer(img=self.vp_img_arr)
self.vp_img_arr = obj.lum_eq()
#self.vp_img_arr = obj.awb_eq()
del obj
# colour and contrast handling
obj = LfpContrast(vp_img_arr=self.vp_img_arr,
cfg=self.cfg,
sta=self.sta,
p_lo=0.0,
p_hi=1.0)
# contrast automation
obj.contrast_bal()
# automatic white balance
if self.cfg.params[self.cfg.opt_awb_]:
obj.auto_wht_bal()
# automatic saturation
if self.cfg.params[self.cfg.opt_sat_]:
obj.sat_bal()
self.vp_img_arr = obj.vp_img_arr
del obj
# remove hot pixels if option is set
if self.cfg.params[self.cfg.opt_hotp]:
obj = LfpHotPixels(vp_img_arr=self.vp_img_arr,
cfg=self.cfg,
sta=self.sta)
obj.main()
self.vp_img_arr = obj.vp_img_arr
del obj
# write viewpoint data to hard drive
if self.cfg.params[self.cfg.opt_view]:
obj = LfpExporter(vp_img_arr=self.vp_img_arr,
cfg=self.cfg,
sta=self.sta)
obj.write_viewpoint_data()
del obj
# print status
self.sta.progress(100, self.cfg.params[self.cfg.opt_prnt])
def shift_and_sum(self):
# refocusing
if not self.sta.interrupt:
obj = LfpShiftAndSum(vp_img_arr=self.vp_img_arr, cfg=self.cfg, sta=self.sta)
obj.main()
self.refo_stack = obj.refo_stack
del obj
# color management automation
if not self.sta.interrupt:
self.refo_stack = LfpContrast().auto_hist_align(self.refo_stack, ref_img=self.refo_stack[0], opt=True)
self.refo_stack = GammaConverter().srgb_conv(img=self.refo_stack)
# write refocused images to hard drive
if not self.sta.interrupt:
obj = LfpExporter(refo_stack=self.refo_stack, cfg=self.cfg, sta=self.sta)
obj.export_refo_stack(file_type='png')
obj.gif_refo()
del obj
def refo_from_vp(self):
""" computational refocusing based on viewpoint shift and integration """
# print status
self.sta.progress(0, self.cfg.params[self.cfg.opt_prnt])
# initialize variables
self._refo_stack = list()
patch_len = self.cfg.params[self.cfg.ptc_leng]
factor = self.cfg.params[self.cfg.ptc_leng] if self.cfg.params[
self.cfg.opt_refi] else 1
# divide intensity to prevent clipping in shift and sum process
self._vp_img_arr /= patch_len
# iterate through refocusing parameter a
ran_refo = self.cfg.params[self.cfg.ran_refo]
a_list = tuple([factor * a for a in ran_refo
]) if self.cfg.params[self.cfg.opt_refi] else ran_refo
for a in range(*a_list):
overlap = abs(a) * (patch_len - 1)
img_slice = np.zeros(
np.append(
np.array(self._vp_img_arr.shape[2:-1]) * factor +
[overlap, overlap], 3))
for j in range(patch_len):
for i in range(patch_len):
# perform sub-pixel refinement if required
vp_img = misc.img_resize(
self._vp_img_arr[j, i],
factor) if factor > 1 else self._vp_img_arr[j, i]
# get viewpoint padding for each border
tb = (abs(a) * j, abs(a) * (patch_len - 1 - j)
) # top, bottom
lr = (abs(a) * i, abs(a) * (patch_len - 1 - i)
) # left, right
# flip padding for each axis if a is negative
pad_width = (tb, lr, (0, 0)) if a >= 0 else (tb[::-1],
lr[::-1], (0,
0))
# shift viewpoint image and add its values to refocused image slice
img_slice = np.add(img_slice,
np.pad(vp_img, pad_width, 'edge'))
# check interrupt status
if self.sta.interrupt:
return False
# print status
percentage = ((j * patch_len + i + 1) / patch_len**2 + a -
a_list[0]) / (a_list[-1] - a_list[0]) * 100
self.sta.progress(percentage,
self.cfg.params[self.cfg.opt_prnt])
# crop refocused image for consistent image dimensions
crop = int(overlap / 2)
final_img = img_slice[crop:-crop,
crop:-crop, :] if (a != 0) else img_slice
# write upscaled version to hard drive
if self.cfg.params[self.cfg.opt_refi]:
upscale_img = LfpContrast().auto_hist_align(final_img.copy(),
ref_img=final_img,
opt=True)
upscale_img = GammaConverter().srgb_conv(img=upscale_img)
fname = np.round(a / patch_len, 2)
LfpExporter(cfg=self.cfg,
sta=self.sta).save_refo_slice(fname,
upscale_img,
string='upscale_')
del upscale_img
# spatially downscale image to original resolution (less memory required)
final_img = misc.img_resize(final_img, 1. /
factor) if factor > 1 else final_img
self._refo_stack.append(final_img)
return True
def main(self):
self.cfg.load_cal_data()
# micro image crop
lfp_obj = LfpCropper(lfp_img_align=self._lfp_img_align, cfg=self.cfg, sta=self.sta)
lfp_obj.main()
self._lfp_img_align = lfp_obj.lfp_img_align
del lfp_obj
# viewpoint images
if self.cfg.params[self.cfg.opt_view] and not self.sta.interrupt:
lfp_obj = LfpRearranger(self._lfp_img_align, cfg=self.cfg, sta=self.sta)
lfp_obj.main()
self.vp_img_arr = lfp_obj.vp_img_arr
del lfp_obj
# histogram equalization
if self.cfg.params[self.cfg.opt_cont] and not self.sta.interrupt:
obj = HistogramEqualizer(img=self.vp_img_arr)
self.vp_img_arr = obj.lum_eq()
#self.vp_img_arr = obj.awb_eq()
del obj
# remove hot pixels if option is set
if self.cfg.params[self.cfg.opt_hotp] and not self.sta.interrupt:
obj = LfpHotPixels(vp_img_arr=self.vp_img_arr, cfg=self.cfg, sta=self.sta)
obj.main()
self.vp_img_arr = obj.vp_img_arr
del obj
# color equalization
if self.cfg.params[self.cfg.opt_colo] and not self.sta.interrupt:
obj = LfpColorEqualizer(vp_img_arr=self.vp_img_arr, cfg=self.cfg, sta=self.sta)
obj.main()
self.vp_img_arr = obj._vp_img_arr
del obj
if not self.sta.interrupt:
obj = LfpContrast(vp_img_arr=self.vp_img_arr, cfg=self.cfg, sta=self.sta, p_lo=0.005, p_hi=0.999)
# automatic white balance
if self.cfg.params[self.cfg.opt_awb_]:
obj.auto_wht_bal()
else:
obj.channel_bal()
obj.p_lo = 0
obj.p_hi = 1
# automatic saturation
if self.cfg.params[self.cfg.opt_sat_]:
obj.sat_bal()
self.vp_img_arr = obj.vp_img_arr
del obj
# write viewpoint data to hard drive
if self.cfg.params[self.cfg.opt_view] and not self.sta.interrupt:
obj = LfpExporter(vp_img_arr=self.vp_img_arr, cfg=self.cfg, sta=self.sta)
obj.write_viewpoint_data()
del obj
return True
def main(self):
self.cfg.load_cal_data()
# micro image crop
lfp_obj = LfpCropper(lfp_img_align=self._lfp_img_align,
cfg=self.cfg,
sta=self.sta)
lfp_obj.main()
self._lfp_img_align = lfp_obj.lfp_img_align
del lfp_obj
# rearrange light-field to sub-aperture images
if self.cfg.params[self.cfg.opt_view] and not self.sta.interrupt:
lfp_obj = LfpRearranger(self._lfp_img_align,
cfg=self.cfg,
sta=self.sta)
lfp_obj.main()
self.vp_img_arr = lfp_obj.vp_img_arr
del lfp_obj
# remove outliers if option is set
if self.cfg.params[self.cfg.opt_lier] and not self.sta.interrupt:
obj = LfpOutliers(vp_img_arr=self.vp_img_arr,
cfg=self.cfg,
sta=self.sta)
obj.main()
self.vp_img_arr = obj.vp_img_arr
del obj
# color equalization
if self.cfg.params[self.cfg.opt_colo] and not self.sta.interrupt:
obj = LfpColorEqualizer(vp_img_arr=self.vp_img_arr,
cfg=self.cfg,
sta=self.sta)
obj.main()
self.vp_img_arr = obj.vp_img_arr
del obj
# copy light-field for refocusing process prior to contrast alignment and export
vp_img_exp = self.vp_img_arr.copy()
# color management automation
if not self.sta.interrupt:
obj = LfpContrast(vp_img_arr=vp_img_exp,
cfg=self.cfg,
sta=self.sta)
obj.main()
vp_img_exp = obj.vp_img_arr
del obj
# reduction of hexagonal sampling artifacts
if self.cfg.params[self.cfg.opt_arti] and not self.sta.interrupt:
obj = HexCorrector(vp_img_arr=vp_img_exp,
cfg=self.cfg,
sta=self.sta)
obj.main()
vp_img_exp = obj.vp_img_arr
del obj
# write viewpoint data to hard drive
if self.cfg.params[self.cfg.opt_view] and not self.sta.interrupt:
obj = LfpExporter(vp_img_arr=vp_img_exp,
cfg=self.cfg,
sta=self.sta)
obj.write_viewpoint_data()
del obj
return True