def __init__(self, parent):
# inheritance
tk.Frame.__init__(self, parent)
self.parent = parent
# instantiate status
self.sta = parent.sta
self.sta.bind_to_interrupt(self.stop_thread)
# instantiate config settings
self.cfg = PlenopticamConfig()
# instantiate menu widget
self.men_wid = MenuWidget(self)
self.men_wid.grid()
# instantiate config widget
self.fil_wid = FileWidget(self)
self.fil_wid.grid(padx=PX, pady=PY)
# instantiate command widget
self.cmd_wid = CmndWidget(self)
self.cmd_wid.grid(padx=PX, pady=PY)
self.all_btn_list = self.cmd_wid.btn_list + self.fil_wid.btn_list + self.men_wid.btn_list
self.var_init()
def setUp(self):
# set config for unit test purposes
self.sta = PlenopticamStatus()
self.cfg = PlenopticamConfig()
self.cfg.reset_values()
self.cfg.params[self.cfg.opt_dbug] = True
self.cfg.params[self.cfg.opt_prnt] = True
def __init__(self, *args, **kwargs):
self.cfg = kwargs['cfg'] if 'cfg' in kwargs else PlenopticamConfig()
self.sta = kwargs['sta'] if 'sta' in kwargs else PlenopticamStatus()
self._bay_img = kwargs['bay_img'] if 'bay_img' in kwargs else np.array(
[])
def __init__(self,
img,
centroids,
cfg=None,
sta=None,
M=None,
method=None):
"""
This class takes a list of integer coordinates as centroids and an intensity map as inputs and re-computes
:param img: image used as basis for coordinate refinement calculation
:param centroids: iterable (list or np.ndarray) with coordinates of integer type
:param cfg: PlenoptiCam configuration object
:param sta: PlenoptiCam status object
:param M: micro image size
:param method: 'area' or 'peak'
"""
# input variables
self._img = img
self._centroids = centroids
self.cfg = cfg if cfg is not None else PlenopticamConfig()
self.sta = sta if sta is not None else PlenopticamStatus()
self._M = M
self._method = method if method is not None else 'area'
# internal variables
self._t = self._s = 0
# output variables
self._centroids_refined = []
def __init__(self, img, centroids, cfg=None, sta=None):
# input variables
self._img = Normalizer(rgb2gray(img.copy())).uint8_norm()
self._centroids = np.asarray(centroids)
self.cfg = cfg if cfg is not None else PlenopticamConfig()
self.sta = sta if sta is not None else PlenopticamStatus()
def __init__(self, *args, **kwargs):
# input variables
self._lfp_img = kwargs['lfp_img'] if 'lfp_img' in kwargs else None
self._wht_img = kwargs['wht_img'] if 'wht_img' in kwargs else None
self.cfg = kwargs['cfg'] if 'cfg' in kwargs else PlenopticamConfig()
self.sta = kwargs['sta'] if 'sta' in kwargs else misc.PlenopticamStatus()
# convert to float
self._lfp_img = self._lfp_img.astype('float64') if self._lfp_img is not None else None
self._wht_img = self._wht_img.astype('float64') if self._wht_img is not None else None
if self.cfg.calibs:
# micro lens array variables
self._CENTROIDS = np.asarray(self.cfg.calibs[self.cfg.mic_list])
self._LENS_Y_MAX = int(max(self._CENTROIDS[:, 2])+1) # +1 to account for index 0
self._LENS_X_MAX = int(max(self._CENTROIDS[:, 3])+1) # +1 to account for index 0
# micro image size evaluation
self._M = self.pitch_max(self.cfg.calibs[self.cfg.mic_list])
self._M = self.pitch_eval(self._M, self.cfg.params[self.cfg.ptc_leng], self.sta)
self._C = self._M//2
try:
self._DIMS = self._lfp_img.shape if len(self._lfp_img.shape) == 3 else self._lfp_img.shape + (1,)
except (TypeError, AttributeError):
pass
except IndexError:
self.sta.status_msg('Incompatible image dimensions: Please either use KxLx3 or KxLx1 array dimensions')
self.sta.error = True
def __init__(self, wht_img, cfg=None, sta=None, M=None):
# input variables
self._wht_img = wht_img
self.cfg = cfg if cfg is not None else PlenopticamConfig()
self.sta = sta if sta is not None else PlenopticamStatus()
self._M = M
def __init__(self, *args, **kwargs):
self._vp_img_arr = kwargs['vp_img_arr'].astype(
'float64') if 'vp_img_arr' in kwargs else None
self.cfg = kwargs['cfg'] if 'cfg' in kwargs else PlenopticamConfig()
self.sta = kwargs['sta'] if 'sta' in kwargs else PlenopticamStatus()
self._M = self.cfg.params[self.cfg.ptc_leng]
def __init__(self, lfp_img_align, cfg=None, sta=None):
self._lfp_img_align = lfp_img_align
self.cfg = cfg if cfg is not None else PlenopticamConfig()
self.sta = sta if sta is not None else misc.PlenopticamStatus()
# internal variable
self._vp_img_arr = []
def setUp(self):
self.root = tk.Tk()
self.cfg = PlenopticamConfig()
self.sta = PlenopticamStatus()
self.root.cfg = self.cfg
self.root.sta = self.sta
self.set_file_path()
self.pump_events()
def __init__(self, cfg=None, sta=None, *args, **kwargs):
super(PropagatingThread, self).__init__(*args, **kwargs)
# init
self.cfg = cfg if cfg is not None else PlenopticamConfig()
self.sta = sta if sta is not None else misc.PlenopticamStatus()
self.exc = None
self.ret = None
def __init__(self, img, cfg=None, sta=None):
# input variables
self._img = img
self.cfg = cfg if cfg is not None else PlenopticamConfig()
self.sta = sta if sta is not None else PlenopticamStatus()
# internal variable
self._map = np.zeros(self._img.shape, dtype=self._img.dtype)
def __init__(self, lfp_img_align=None, cfg=None, sta=None):
# input variables
self._lfp_img_align = lfp_img_align
self.cfg = cfg if cfg is not None else PlenopticamConfig()
self.sta = sta if sta is not None else misc.PlenopticamStatus()
# variables for viewpoint arrays
self.vp_img_arr = [] # gamma corrected
self.vp_img_linear = [] # linear gamma (for further processing)
def __init__(self, lfp_img, mic_list, rad=None, cfg=None, sta=None):
# input and output variable
self._lfp_img = lfp_img
self.cfg = cfg if cfg is not None else PlenopticamConfig()
self.sta = sta if sta is not None else PlenopticamStatus()
# internal variables
self._centroids = np.asarray(mic_list)
self._rad = rad
def __init__(self, img, cfg=None, sta=None, M=None):
# input variables
self._img = img
self.cfg = cfg if cfg is not None else PlenopticamConfig()
self.sta = sta if sta is not None else PlenopticamStatus()
self._M = M if M is not None else self.cfg.params[self.cfg.ptc_leng]
# private variables
self._peak_img = self._img.copy()
self._centroids = []
def __init__(self, img, cfg, sta=None, M=None, method=None):
# input variables
self._img = img
self.cfg = cfg if cfg is not None else PlenopticamConfig()
self.sta = sta if sta is not None else PlenopticamStatus()
self._M = M if M is not None else 9
self._method = method if method is not None else 'area'
# private variables
self._peak_img = self._img.copy()
self._centroids = []
def setUp(self):
# instantiate config and status objects
self.cfg = PlenopticamConfig()
self.cfg.default_values()
self.sta = PlenopticamStatus()
# enable options in config to cover more algorithms in tests
self.cfg.params[self.cfg.cal_meth] = 'grid-fit'
self.cfg.params[self.cfg.opt_vign] = True
self.cfg.params[self.cfg.opt_rota] = True
self.cfg.params[self.cfg.opt_refi] = True
self.cfg.params[self.cfg.opt_pflu] = True
self.cfg.params[self.cfg.opt_arti] = True
self.cfg.params[self.cfg.opt_lier] = True
self.cfg.params[self.cfg.opt_cont] = True
self.cfg.params[self.cfg.opt_awb_] = True
self.cfg.params[self.cfg.opt_sat_] = True
self.cfg.params[self.cfg.opt_dbug] = True
self.cfg.params[self.cfg.ran_refo] = [0, 1]
# compute 3x3 viewpoints only (to reduce computation time)
self.cfg.params[self.cfg.ptc_leng] = 3
# skip progress prints (prevent Travis from terminating due to reaching 4MB logfile size)
self.sta.prog_opt = False
# print current process message (to prevent Travis from stopping after 10 mins)
self.cfg.params[self.cfg.opt_prnt] = True
# retrieve Lytro Illum data
self.loader = DataDownloader(cfg=self.cfg, sta=self.sta)
self.fp = join(self.loader.root_path, 'examples', 'data')
archive_fn = join(self.fp, basename(self.loader.host_eu_url))
self.loader.download_data(
self.loader.host_eu_url,
fp=self.fp) if not exists(archive_fn) else None
self.loader.extract_archive(archive_fn)
def __init__(self, *args, **kwargs):
tk.Canvas.__init__(self, *args, **kwargs)
LfpViewpoints.__init__(self, *args, **kwargs)
# app reltated data
self.cfg = kwargs['cfg'] if 'cfg' in kwargs else PlenopticamConfig()
self.sta = kwargs['sta'] if 'sta' in kwargs else PlenopticamStatus()
# window dimensions
self._ht = self.winfo_screenheight()
self._wd = self.winfo_screenwidth()
# window settings
# self['bg'] = "white"
self.master.title("PlenoptiCam Viewer")
vp_dirs = glob.glob(os.path.join(self.cfg.exp_path, 'viewpoints_*px'))
rf_dirs = glob.glob(os.path.join(self.cfg.exp_path, 'refo_*px'))
try:
self.vp_img_arr = kwargs[
'vp_img_arr'] if 'vp_img_arr' in kwargs else get_list(
vp_dirs[0], vp=1)
self.refo_stack = kwargs[
'refo_stack'] if 'refo_stack' in kwargs else get_list(
rf_dirs[0], vp=0)
except Exception as e:
print(e)
self.sta.status_msg(msg='\nNo valid image data found',
opt=self.cfg.opt_prnt)
if hasattr(self, 'vp_img_arr'):
# light-field related data
self._M = self.cfg.params[
self.cfg.ptc_leng] #self.vp_img_arr.shape[0] #
self._v = self._u = self._C = self._M // 2
self._a = 0
self._k = -1
self.move_coords = self.get_move_coords(
pattern='circle', arr_dims=self.vp_img_arr.shape[:2])
# initialize member variables
self.vp_mode = True
self.auto_mode = False
self._mode_text = tk.StringVar()
self._mode_text.set('VP' if self.vp_mode else 'RF')
self.all_function_trigger()
# display initial image
self.next_frame()
def __init__(self, img, cfg=None, sta=None, scale_val=1.625, CR=3):
# input variables
self._img = img
self.cfg = cfg if cfg is not None else PlenopticamConfig()
self.sta = sta if sta is not None else PlenopticamStatus()
self._scale_val = scale_val
self._CR = CR
# internal variables
self._top_img = None
# output variables
self._M = None
self.scale_space = []
def __init__(self, *args, **kwargs):
# instantiate config and status objects
self.cfg = kwargs['cfg'] if 'cfg' in kwargs else PlenopticamConfig()
self.sta = kwargs['sta'] if 'sta' in kwargs else PlenopticamStatus()
# path handling: refer to folder where data will be stored
path = kwargs['path'] if 'path' in kwargs else os.path.dirname(os.path.abspath(__file__))
self._fp = os.path.join(path, 'data')
self.root_path = dirname(abspath('.')) if basename((abspath('.'))) == 'tests' else abspath('.')
# data urls
self.host_eu_url = 'http://wp12283669.server-he.de/Xchange/illum_test_data.zip'
self.opex_url = 'https://ndownloader.figshare.com/files/5201452'
self.opex_fnames_wht = ['f197with4m11pxf16Final.bmp', 'f197Inf9pxFinalShift12.7cmf22.bmp']
self.opex_fnames_lfp = ['f197with4m11pxFinal.bmp', 'f197Inf9pxFinalShift12.7cm.bmp']
def __init__(self, centroids, cfg=None, sta=None, bbox=None):
# input variables
self._centroids = np.asarray(centroids) # list of unsorted maxima
self.cfg = cfg if cfg is not None else PlenopticamConfig()
self.sta = sta if sta is not None else PlenopticamStatus()
self._bbox = bbox if bbox is not None and len(bbox) == 2 else None
# internal variables
self._lens_x_max = None # maximum number of "complete" micro image centers in a row
self._lens_y_max = None # maximum number of "complete" micro image centers in a column
self._upper_l = None
self._lower_r = None
# output variables
self._mic_list = [] # list of micro image centers with indices assigned
self._pattern = None # pattern typ of micro lens array
self._pitch = None # average pitch in horizontal and vertical direction
def __init__(self, file=None, cfg=None, sta=None, **kwargs):
# input variables
self.cfg = cfg if cfg is not None else PlenopticamConfig()
self.sta = sta if sta is not None else PlenopticamStatus()
self.file = file
self._lfp_path = kwargs[
'lfp_path'] if 'lfp_path' in kwargs else self.cfg.params[
self.cfg.lfp_path]
# internal variables
self._json_dict = kwargs['json_dict'] if 'json_dict' in kwargs else {}
self._shape = None
self._img_buf = None
# output variable
self.cfg.lfpimg = {} if not hasattr(self.cfg,
'lfpimg') else self.cfg.lfpimg
self._bay_img = None
def __init__(self, *args, **kwargs):
self._vp_img_arr = kwargs['vp_img_arr'].astype(
'float64') if 'vp_img_arr' in kwargs else None
self.cfg = kwargs['cfg'] if 'cfg' in kwargs else PlenopticamConfig()
self.sta = kwargs['sta'] if 'sta' in kwargs else PlenopticamStatus()
self._M = self.cfg.params[self.cfg.ptc_leng]
self._C = self._M // 2
try:
self._DIMS = self._vp_img_arr.shape if len(
self._vp_img_arr.shape) == 3 else self._vp_img_arr.shape + (
1, )
except (TypeError, AttributeError):
pass
except IndexError:
self.sta.status_msg(
'Incompatible image dimensions: Please either use KxLx3 or KxLx1 array dimensions'
)
self.sta.error = True
def __init__(self, bay_img=None, wht_img=None, cfg=None, sta=None):
# input variables
self.cfg = cfg if cfg is not None else PlenopticamConfig()
self.sta = sta if sta is not None else misc.PlenopticamStatus()
self._bay_img = bay_img.astype('float32') if isinstance(
bay_img, np.ndarray) else None
self._wht_img = wht_img.astype('float32') if isinstance(
wht_img, np.ndarray) else None
self._bit_pac = self.cfg.lfpimg[
'bit'] if 'bit' in self.cfg.lfpimg else 10
self._gains = self.cfg.lfpimg['awb'] if 'awb' in self.cfg.lfpimg else [
1, 1, 1, 1
]
self._bay_pat = self.cfg.lfpimg[
'bay'] if 'bay' in self.cfg.lfpimg else None
# output variables
self._rgb_img = np.array([])
def __init__(self, cfg=None, sta=None):
# input variables
self.cfg = cfg if sta is not None else PlenopticamConfig()
self.sta = sta if sta is not None else PlenopticamStatus()
# internal variables
self._lfp_json = {}
self._georef = None
self._lensref = None
self._serial = None
self._cam_model = ''
self._cal_fn = None
self._raw_data = None
self._file_found = None
self._opt_prnt = True if sta is not None else self.cfg.params[
self.cfg.opt_prnt]
self._path = self.cfg.params[self.cfg.cal_path]
# output variables
self._wht_bay = None
def __init__(self, *args, **kwargs):
# input variables
self._lfp_img = kwargs['lfp_img'] if 'lfp_img' in kwargs else None
self._wht_img = kwargs['wht_img'] if 'wht_img' in kwargs else None
self.cfg = kwargs['cfg'] if 'cfg' in kwargs else PlenopticamConfig()
self.sta = kwargs['sta'] if 'sta' in kwargs else PlenopticamStatus()
# add 3rd axis for 2D image
self._lfp_img = self._lfp_img[..., np.newaxis] if len(self._lfp_img.shape) == 2 else self._lfp_img
# convert to float
self._lfp_img = self._lfp_img.astype('float64')
self._wht_img = self._wht_img.astype('float64')
self._CENTROIDS = np.asarray(self.cfg.calibs[self.cfg.mic_list])
self._M = LfpCropper.pitch_max(self.cfg.calibs[self.cfg.mic_list])
self._C = int((self._M-1)/2)
self._LENS_Y_MAX = int(max(self._CENTROIDS[:, 2]))
self._LENS_X_MAX = int(max(self._CENTROIDS[:, 3]))
self._DIMS = self._lfp_img.shape if len(self._lfp_img.shape) == 3 else None
def __init__(self, *args, **kwargs):
# input variables
self._lfp_img = kwargs['lfp_img'] if 'lfp_img' in kwargs else None
self._wht_img = kwargs['wht_img'] if 'wht_img' in kwargs else None
self.cfg = kwargs['cfg'] if 'cfg' in kwargs else PlenopticamConfig()
self.sta = kwargs[
'sta'] if 'sta' in kwargs else misc.PlenopticamStatus()
# convert to float
self._lfp_img = self._lfp_img.astype(
'float64') if self._lfp_img is not None else None
self._wht_img = self._wht_img.astype(
'float64') if self._wht_img is not None else None
# micro lens array variables
self._CENTROIDS = np.asarray(self.cfg.calibs[self.cfg.mic_list])
self._LENS_Y_MAX = int(max(self._CENTROIDS[:, 2]) +
1) # +1 to account for index 0
self._LENS_X_MAX = int(max(self._CENTROIDS[:, 3]) +
1) # +1 to account for index 0
# micro image size evaluation
self._M = self.pitch_max(self.cfg.calibs[self.cfg.mic_list])
self._M = self.pitch_eval(self._M, self.cfg.params[self.cfg.ptc_leng],
self.sta)
self._C = self._M // 2
if self._lfp_img is not None:
# get light field dimensions
self._DIMS = self._lfp_img.shape
# add 3rd axis for 2D image
self._lfp_img = self._lfp_img[..., np.newaxis] if len(
self._lfp_img.shape) == 2 else self._lfp_img
import numpy as np from plenopticam.cfg import PlenopticamConfig cfg = PlenopticamConfig() cfg.params[cfg.cal_meta] = "" cfg.load_cal_data() mic_list = np.asarray(cfg.calibs[cfg.mic_list]) from plenopticam.misc import PlenopticamStatus sta = PlenopticamStatus() # do grid fitting from plenopticam.lfp_calibrator import GridFitter obj = GridFitter(cfg=cfg, sta=sta) obj.main() new_list = np.asarray(obj.grid_fit) # plot import matplotlib.pyplot as plt plt.figure() plt.plot(mic_list[:, 1], mic_list[:, 0], 'rx') plt.plot(new_list[:, 1], new_list[:, 0], 'b+') plt.show()
def main():
# program info
print("\nPlenoptiCam v%s \n" % __version__)
# create config object
cfg = PlenopticamConfig()
cfg.default_values()
# parse options
cfg = parse_options(sys.argv[1:], cfg)
# instantiate status object
sta = misc.PlenopticamStatus()
sta.bind_to_interrupt(sys.exit) # set interrupt
# force relative paths to be absolute
cfg.params[cfg.lfp_path] = os.path.abspath(cfg.params[cfg.lfp_path])
cfg.params[cfg.cal_path] = os.path.abspath(cfg.params[cfg.cal_path])
# collect light field image file name(s) based on provided path
if os.path.isdir(cfg.params[cfg.lfp_path]):
lfp_filenames = [
f for f in os.listdir(cfg.params[cfg.lfp_path])
if f.lower().endswith(SUPP_FILE_EXT)
]
cfg.params[cfg.lfp_path] = os.path.join(cfg.params[cfg.lfp_path],
'dummy.ext')
elif not os.path.isfile(cfg.params[cfg.lfp_path]):
lfp_filenames = [
misc.select_file(cfg.params[cfg.lfp_path],
'Select plenoptic image')
]
else:
lfp_filenames = [cfg.params[cfg.lfp_path]]
if not cfg.params[cfg.cal_path]:
# manual calibration data selection
sta.status_msg(
'\r Please select white image calibration source manually',
cfg.params[cfg.opt_prnt])
# open selection window (at current lfp file directory) to set calibration folder path
cfg.params[cfg.cal_path] = misc.select_file(
cfg.params[cfg.lfp_path], 'Select calibration image')
# provide number of found images to user
print("\n %s Image(s) found" % len(lfp_filenames))
# cancel if file paths not provided
sta.validate(checklist=lfp_filenames + [cfg.params[cfg.lfp_path]],
msg='Canceled due to missing image file path')
# iterate through light field image(s)
for lfp_filename in sorted(lfp_filenames):
# change path to next filename
cfg.params[cfg.lfp_path] = os.path.join(
os.path.dirname(cfg.params[cfg.lfp_path]), lfp_filename)
print(cfg.params[cfg.lfp_path])
sta.status_msg(msg='Process file ' + lfp_filename,
opt=cfg.params[cfg.opt_prnt])
# remove output folder if option is set
misc.rmdir_p(cfg.exp_path) if cfg.params[cfg.dir_remo] else None
try:
# decode light field image
lfp_obj = lfp_reader.LfpReader(cfg, sta)
lfp_obj.main()
lfp_img = lfp_obj.lfp_img
del lfp_obj
except Exception as e:
misc.PlenopticamError(e)
continue
# create output data folder
misc.mkdir_p(cfg.exp_path, cfg.params[cfg.opt_prnt])
if cfg.cond_auto_find():
# automatic calibration data selection
obj = lfp_calibrator.CaliFinder(cfg, sta)
obj.main()
wht_img = obj.wht_bay
del obj
else:
# load white image calibration file
wht_img = misc.load_img_file(cfg.params[cfg.cal_path])
# save settings configuration
cfg.save_params()
# perform calibration if previously computed calibration data does not exist
meta_cond = not (os.path.exists(cfg.params[cfg.cal_meta])
and cfg.params[cfg.cal_meta].lower().endswith('json'))
if meta_cond or cfg.params[cfg.opt_cali]:
# perform centroid calibration
cal_obj = lfp_calibrator.LfpCalibrator(wht_img, cfg, sta)
cal_obj.main()
cfg = cal_obj.cfg
del cal_obj
# load calibration data
cfg.load_cal_data()
# check if light field alignment has been done before
if cfg.cond_lfp_align():
# align light field
lfp_obj = lfp_aligner.LfpAligner(lfp_img, cfg, sta, wht_img)
lfp_obj.main()
lfp_obj = lfp_obj.lfp_img
del lfp_obj
# load previously computed light field alignment
with open(os.path.join(cfg.exp_path, 'lfp_img_align.pkl'), 'rb') as f:
lfp_img_align = pickle.load(f)
# extract viewpoint data
lfp_calibrator.CaliFinder(cfg).main()
obj = lfp_extractor.LfpExtractor(lfp_img_align, cfg=cfg, sta=sta)
obj.main()
vp_img_arr = obj.vp_img_arr
del obj
# do refocusing
if cfg.params[cfg.opt_refo]:
obj = lfp_refocuser.LfpRefocuser(vp_img_arr, cfg=cfg, sta=sta)
obj.main()
del obj
return True
from plenopticam.misc import PlenopticamStatus, load_img_file
from plenopticam.cfg import PlenopticamConfig, constants
import numpy as np
import matplotlib.pyplot as plt
from color_space_converter import rgb2gry
# Text rendering with LaTeX
from matplotlib import rc
rc('font', **{'family': 'sans-serif', 'sans-serif': ['Helvetica']})
rc('text', usetex=True)
# for Palatino
# rc('font',**{'family':'serif','serif':['Palatino']})
# plenopticam objects
cfg = PlenopticamConfig()
sta = PlenopticamStatus()
# file settings
fname = './c'
cfg.params[cfg.cal_path] = fname + '.png'
cfg.params[cfg.cal_meth] = constants.CALI_METH[2] #'peak' #
wht_img = load_img_file(cfg.params[cfg.cal_path])
crop = True
# load ground truth (remove outlying centers)
spots_grnd_trth = np.loadtxt(fname + '.txt')
spots_grnd_trth = spots_grnd_trth[spots_grnd_trth[:, 1] > 0]
spots_grnd_trth = spots_grnd_trth[spots_grnd_trth[:, 0] > 0]
spots_grnd_trth = spots_grnd_trth[spots_grnd_trth[:, 1] < wht_img.shape[1]]
spots_grnd_trth = spots_grnd_trth[spots_grnd_trth[:, 0] < wht_img.shape[0]]
