def _raw2img(self):
''' decode raw data to obtain bayer image and settings data '''
# skip if calibrated json file already exists, otherwise perform centroid calibration
if self._raw_data:
from plenopticam.lfp_reader.lfp_decoder import LfpDecoder
# decode raw data
obj = LfpDecoder(self._raw_data, self.cfg, self.sta)
obj.decode_raw()
self._wht_img = obj.rgb_img
del obj
return True
def _raw2img(self):
''' decode raw data to obtain bayer image and settings data '''
# skip if calibrated json file already exists, otherwise perform centroid calibration
if self._raw_data:
# decode raw data
obj = LfpDecoder(self._raw_data, self.cfg, self.sta)
obj.decode_raw()
self._wht_bay = obj.bay_img
del obj
# balance Bayer channels in white image
try:
wht_json = json.loads(self._wht_json.read())
frame_arr = safe_get(wht_json, 'master', 'picture',
'frameArray')[0]
self.cfg.lfpimg['ccm_wht'] = safe_get(frame_arr, 'frame',
'metadata', 'image',
'color',
'ccmRgbToSrgbArray')
awb = safe_get(frame_arr, 'frame', 'metadata', 'devices',
'sensor', 'normalizedResponses')[0]
gains = [
1. / awb['b'], 1. / awb['r'], 1. / awb['gr'],
1. / awb['gb']
]
self.cfg.lfpimg['awb_wht'] = gains
except ValueError:
gains = [
1 / 0.74476742744445801, 1 / 0.76306647062301636, 1, 1
]
# apply white balance gains to calibration file
cfa_obj = CfaProcessor(bay_img=self._wht_bay,
cfg=self.cfg,
sta=self.sta)
cfa_obj.set_gains(gains)
self._wht_bay = cfa_obj.apply_awb()
del cfa_obj
return True
def main(self):
if self._lfp_path.endswith(('.lfp', '.lfr', '.raw') + tuple('.c.'+str(num) for num in (0, 1, 2, 3))):
# filename and file path from previously decoded data
dp = os.path.splitext(self._lfp_path)[0]
fn = os.path.basename(dp)+'.tiff'
fp = os.path.join(dp, fn)
# load previously generated tiff if present
if os.path.exists(fp):
try:
self._lfp_img = misc.load_img_file(fp)
except TypeError as e:
self.sta.status_msg(e, self.cfg.params[self.cfg.opt_prnt])
self.sta.progress(100, self.cfg.params[self.cfg.opt_prnt])
raise LfpTypeError(e)
except FileNotFoundError as e:
# print status
self.sta.status_msg('File {0} not found'.format(self._lfp_path), self.cfg.params[self.cfg.opt_prnt])
self.sta.progress(100, self.cfg.params[self.cfg.opt_prnt])
raise PlenopticamError(e)
else:
try:
# Lytro type decoding
with open(self._lfp_path, mode='rb') as file:
# print status
self.sta.status_msg('Decode Lytro image file', self.cfg.params[self.cfg.opt_prnt])
self.sta.progress(None, self.cfg.params[self.cfg.opt_prnt])
# LFC and raw type decoding
obj = LfpDecoder(file, self.cfg, self.sta)
if self._lfp_path.endswith(('.lfp', '.lfr') + tuple('.c.'+str(num) for num in (0, 1, 2, 3))):
# LFC type decoding
obj.decode_lfc()
self.cfg.save_json(os.path.join(dp, os.path.basename(dp)+'.json'), json_dict=obj.json_dict)
elif self._lfp_path.endswith('.raw'):
# raw type decoding
obj.decode_raw()
self._lfp_img = obj.rgb_img
del obj
# save bayer image as file
misc.save_img_file(misc.uint16_norm(self._lfp_img), fp, type='tiff')
# print status
self.sta.progress(100, self.cfg.params[self.cfg.opt_prnt])
except FileNotFoundError as e:
# print status
self.sta.status_msg('File {0} not found'.format(self._lfp_path), self.cfg.params[self.cfg.opt_prnt])
self.sta.progress(100, self.cfg.params[self.cfg.opt_prnt])
raise PlenopticamError(e)
else:
try:
# read and decode generic image file type
self._lfp_img = misc.load_img_file(self._lfp_path)
except TypeError as e:
raise LfpTypeError(e)
try:
# try to load json file (if present)
json_dict = self.cfg.load_json(self._lfp_path)
self.cfg.lfpimg = LfpDecoder.filter_json(json_dict)
except:
pass
# write json file
self.cfg.save_params()
return True
def main(self):
if self._lfp_path.lower().endswith(SUPP_FILE_EXT):
# filename and file path from previously decoded data
dp = os.path.splitext(self._lfp_path)[0]
fn = os.path.basename(dp) + '.tiff'
fp = os.path.join(dp, fn)
# load previously generated tiff if present
if os.path.exists(fp):
try:
self._lfp_img = misc.load_img_file(fp)
except FileNotFoundError:
# print status
self.sta.status_msg(
'{0} not found'.format(os.path.basename(
self._lfp_path)),
self.cfg.params[self.cfg.opt_prnt])
self.sta.progress(100, self.cfg.params[self.cfg.opt_prnt])
self.sta.error = True
except TypeError as e:
self.sta.status_msg(e, self.cfg.params[self.cfg.opt_prnt])
self.sta.progress(100, self.cfg.params[self.cfg.opt_prnt])
raise LfpTypeError(e)
else:
try:
# Lytro type decoding
with open(self._lfp_path, mode='rb') as file:
# LFC and raw type decoding
obj = LfpDecoder(file, self.cfg, self.sta)
if self._lfp_path.lower().endswith(SUPP_FILE_EXT[1:]):
# LFC type decoding
obj.decode_lfc()
self.cfg.save_json(os.path.join(
dp,
os.path.basename(dp) + '.json'),
json_dict=obj.json_dict)
elif self._lfp_path.lower().endswith(SUPP_FILE_EXT[0]):
# raw type decoding
obj.decode_raw()
self._lfp_img = obj.rgb_img
del obj
# save bayer image as file
self.sta.status_msg(
msg='Save raw image',
opt=self.cfg.params[self.cfg.opt_prnt])
self.sta.progress(None,
self.cfg.params[self.cfg.opt_prnt])
misc.save_img_file(misc.Normalizer(
self._lfp_img).uint16_norm(),
fp,
file_type='tiff')
self.sta.progress(100,
self.cfg.params[self.cfg.opt_prnt])
except FileNotFoundError:
# print status
self.sta.status_msg(
'{0} not found'.format(os.path.basename(
self._lfp_path)),
self.cfg.params[self.cfg.opt_prnt])
self.sta.progress(100, self.cfg.params[self.cfg.opt_prnt])
self.sta.error = True
except Exception as e:
# unrecognized LFP file type
if not obj.json_dict:
raise LfpTypeError(e)
else:
raise PlenopticamError(e)
else:
try:
# read and decode generic image file type
self._lfp_img = misc.load_img_file(self._lfp_path)
except TypeError as e:
raise LfpTypeError(e)
try:
# try to load json file (if present)
json_dict = self.cfg.load_json(self._lfp_path)
self.cfg.lfpimg = LfpDecoder.filter_json(json_dict)
except:
pass
# write json file
self.cfg.save_params()
return True