def convert_rgb2gray(i_info,
i_sect,
j_sect,
n_rows,
n_cols,
the_sensor,
stats=False):
"""
Converts RGB to gray scale array
Args:
i_info (object of ropen)
j_sect (int): Starting column index.
i_sect (int): Starting row index.
n_cols (int)
n_rows (int)
the_sensor (str): The satellite sensor.
stats (Optional[bool])
Equation:
0.2125 R + 0.7154 G + 0.0721 B
"""
utils.sensor_wavelength_check(the_sensor, ['blue', 'green', 'red'])
bands2open = [
utils.SENSOR_BAND_DICT[the_sensor]['blue'],
utils.SENSOR_BAND_DICT[the_sensor]['green'],
utils.SENSOR_BAND_DICT[the_sensor]['red']
]
if stats:
logger.info('\nCalculating image min and max ...\n')
min_max = get_layer_min_max(i_info, rgb=True)
im_min = min_max[0][0]
im_max = min_max[0][1]
# im_min = 1000000
# im_max = -1000000
#
# for i_ in range(0, i_info.rows, 512):
#
# n_rows_ = raster_tools.n_rows_cols(i_, 512, i_info.rows)
#
# for j_ in range(0, i_info.cols, 512):
#
# n_cols_ = raster_tools.n_rows_cols(j_, 512, i_info.cols)
#
# im_block = i_info.read(bands2open=[1, 2, 3],
# i=i_, j=j_,
# rows=n_rows_, cols=n_cols_,
# d_type='float32')
#
# luminosity = get_luminosity(im_block, n_rows_, n_cols_, rgb)
#
# im_min, im_max = min_max_func(luminosity, im_min, im_max)
# bp = raster_tools.BlockFunc(min_max_func, [i_info], None, None,
# out_attributes=['im_min', 'im_max'],
# print_statement='\nGetting image statistics ...\n',
# write_array=False,
# close_files=False,
# be_quiet=False)
#
# bp.run()
return None, im_min, im_max
else:
logger.info('\nCalculating average RGB ...\n')
im_block = i_info.read(bands2open=bands2open,
i=i_sect,
j=j_sect,
rows=n_rows,
cols=n_cols,
d_type='float32')
luminosity = get_luminosity(im_block)
return luminosity, None, None
def _section_read_write(section_counter):
"""
Handles the section reading and writing
Args:
section_counter (int)
"""
section_pair = potsi[section_counter - 1]
# this_parameter_object_ = this_parameter_object.copy()
this_parameter_object_ = copy.copy(param_dict)
this_parameter_object_ = sputilities.dict2class(this_parameter_object_)
# Get the input image information.
with raster_tools.ropen(
this_parameter_object_.input_image) as this_image_info:
this_parameter_object_.update_info(section_counter=section_counter)
# Set the output name.
this_parameter_object_ = sputilities.scale_fea_check(
this_parameter_object_)
# Open the status YAML file.
mts_ = sputilities.ManageStatus()
# Load the status dictionary
mts_.load_status(this_parameter_object_.status_file)
# Check file status.
if os.path.isfile(this_parameter_object_.out_img):
if this_parameter_object_.out_img_base in mts_.status_dict:
if this_parameter_object_.trigger in mts_.status_dict[
this_parameter_object_.out_img_base]:
# Check every trigger because the
# entire file needs to be removed.
status_list = [
mts_.status_dict[this_parameter_object_.out_img_base]
['{TR}-{BD}'.format(
TR=tr, BD=this_parameter_object_.band_position)]
for tr in this_parameter_object_.triggers
]
if 'corrupt' in status_list:
logger.info('Re-running {} ...'.format(
this_parameter_object_.out_img))
# Remove the file on the first trigger
# if the file is corrupt.
if this_parameter_object_.trigger == this_parameter_object_.triggers[
0]:
os.remove(this_parameter_object_.out_img)
mts_.status_dict[this_parameter_object_.out_img_base][
'{TR}-{BD}'.format(
TR=this_parameter_object_.trigger,
BD=this_parameter_object_.band_position
)] = 'incomplete'
mts_.dump_status(this_parameter_object_.status_file)
elif ('corrupt' not in status_list) and ('incomplete'
in status_list):
logger.info('Re-running {} ...'.format(
this_parameter_object_.out_img))
else:
if this_parameter_object_.overwrite:
logger.info('Re-running {} ...'.format(
this_parameter_object_.out_img))
# Remove the file on the first trigger.
if this_parameter_object_.trigger == this_parameter_object_.triggers[
0]:
os.remove(this_parameter_object_.out_img)
mts_.status_dict[
this_parameter_object_.out_img_base][
'{TR}-{BD}'.format(
TR=this_parameter_object_.trigger,
BD=this_parameter_object_.band_position
)] = 'incomplete'
mts_.dump_status(
this_parameter_object_.status_file)
else:
logger.info('{} is already finished ...'.format(
this_parameter_object_.out_img))
return
else:
# Remove the file on the first trigger.
if this_parameter_object_.trigger == this_parameter_object_.triggers[
0]:
os.remove(this_parameter_object_.out_img)
logger.info('Re-running {} ...'.format(
this_parameter_object_.out_img))
i_sect = section_pair[0]
j_sect = section_pair[1]
# Row and column section bounds checking
n_rows = raster_tools.n_rows_cols(i_sect,
this_parameter_object_.sect_row_size,
this_image_info.rows)
n_cols = raster_tools.n_rows_cols(j_sect,
this_parameter_object_.sect_col_size,
this_image_info.cols)
# Open the image array.
if this_parameter_object_.trigger.upper(
) in this_parameter_object_.spectral_indices:
wavelengths = utils.VI_WAVELENGTHS[
this_parameter_object_.trigger.upper()]
# Check if the sensor supports the spectral index
utils.sensor_wavelength_check(this_parameter_object_.sat_sensor,
wavelengths)
# Get the band positions needed
# to process the spectral index.
spectral_bands = utils.get_index_bands(
this_parameter_object_.trigger,
this_parameter_object_.sat_sensor)
sect_in = this_image_info.read(bands2open=spectral_bands,
i=i_sect,
j=j_sect,
rows=n_rows,
cols=n_cols,
d_type='float32')
sect_in[sect_in >= this_parameter_object_.
image_max] = this_parameter_object_.image_max
sect_in /= this_parameter_object_.image_max
vie = VegIndicesEquations(sect_in, chunk_size=-1)
sect_in = vie.compute(this_parameter_object_.trigger.upper(),
out_type=1)
this_parameter_object_.update_info(image_min=0, image_max=1)
elif this_parameter_object_.trigger == 'saliency':
sect_in = saliency(this_image_info, this_parameter_object_, i_sect,
j_sect, n_rows, n_cols)
this_parameter_object_.update_info(image_min=0, image_max=255)
elif this_parameter_object_.trigger == 'seg':
sect_in = this_image_info.read(bands2open=[1, 2, 3],
i=i_sect,
j=j_sect,
rows=n_rows,
cols=n_cols)
sect_in = segment_image(sect_in, this_parameter_object_)
elif this_parameter_object_.trigger == 'grad':
if this_image_info.bands >= 3:
sect_in = sputilities.convert_rgb2gray(
this_image_info, i_sect, j_sect, n_rows, n_cols,
this_parameter_object_.sat_sensor)[0]
else:
sect_in = this_image_info.read(
bands2open=this_parameter_object_.band_position,
i=i_sect,
j=j_sect,
rows=n_rows,
cols=n_cols)
sect_in = get_mag_avg(sect_in)
this_parameter_object_.update_info(image_min=0, image_max=30)
elif this_parameter_object_.use_rgb and this_parameter_object_.trigger \
not in this_parameter_object_.spectral_indices + ['grad', 'saliency', 'seg']:
sect_in = sputilities.convert_rgb2gray(
this_image_info, i_sect, j_sect, n_rows, n_cols,
this_parameter_object_.sat_sensor)[0]
else:
sect_in = this_image_info.read(
bands2open=this_parameter_object_.band_position,
i=i_sect,
j=j_sect,
rows=n_rows,
cols=n_cols)
if this_parameter_object_.trigger == 'dmp':
# The Differential Morphological Profile
# is a [D x M x N] array
# where,
# D = the opening/closing derivative.
sect_in = get_dmp(sect_in, this_parameter_object_.image_min,
this_parameter_object_.image_max)
if this_parameter_object_.trigger == 'gabor':
sect_in = convolve_gabor(sect_in, this_parameter_object_.image_min,
this_parameter_object_.image_max,
this_parameter_object_.scales)
if this_parameter_object_.trigger == 'orb':
sect_in = get_orb_keypoints(sect_in,
this_parameter_object_.image_min,
this_parameter_object_.image_max)
this_parameter_object_.update_info(i_sect_blk_ctr=1, j_sect_blk_ctr=1)
if this_parameter_object_.trigger in ['dmp', 'gabor']:
l_rows, l_cols = sect_in[0].shape
else:
l_rows, l_cols = sect_in.shape
# Compute section statistics.
section_stats_array = spsplit.get_section_stats(
sect_in, l_rows, l_cols, this_parameter_object_, section_counter)
# Get the section output rows and columns.
out_rows, out_cols = spsplit.get_out_dims(l_rows, l_cols,
this_parameter_object_)
# Reshape the list of features into
# <features x rows x columns> array.
out_section_array = spreshape.reshape_feature_list(
section_stats_array, out_rows, out_cols, this_parameter_object_)
is_corrupt = _write_section2file(this_parameter_object_,
this_image_info, out_section_array,
i_sect, j_sect, out_rows, out_cols,
section_counter)
this_parameter_object_ = None
this_image_info_ = None
return is_corrupt