def __init__(self, **kwargs):
"""
the parent __init__ method automatically populates this
instance with attributes from the form
"""
super(DataIngestion, self).__init__(**kwargs)
self.random_indices = None
if not 'seed' in self.userdata:
# choose random seed and add to userdata so it gets persisted
self.userdata['seed'] = random.randint(0, 1000)
random.seed(self.userdata['seed'])
# open first image in label folder to retrieve palette
# all label images must use the same palette - this is enforced
# during dataset creation
filename = self.make_image_list(self.label_folder)[0]
image = self.load_label(filename)
self.userdata[COLOR_PALETTE_ATTRIBUTE] = image.getpalette()
# get labels if those were provided
if self.class_labels_file:
with open(self.class_labels_file) as f:
self.userdata['class_labels'] = f.read().splitlines()
def __init__(self, **kwargs):
"""
the parent __init__ method automatically populates this
instance with attributes from the form
"""
super(DataIngestion, self).__init__(**kwargs)
self.random_indices = None
if 'seed' not in self.userdata:
# choose random seed and add to userdata so it gets persisted
self.userdata['seed'] = random.randint(0, 1000)
if 'colormap_method' not in self.userdata:
self.userdata['colormap_method'] = 'label'
random.seed(self.userdata['seed'])
if self.userdata['colormap_method'] == "label":
# open first image in label folder to retrieve palette
# all label images must use the same palette - this is enforced
# during dataset creation
filename = self.text_image_list('label_file')[0]
image = self.load_label(filename)
self.userdata[COLOR_PALETTE_ATTRIBUTE] = image.getpalette()
else:
# read colormap from file
with open(self.colormap_text_file) as f:
palette = []
lines = f.read().splitlines()
for line in lines:
for val in line.split():
try:
palette.append(int(val))
except:
raise ValueError("Your color map file seems to "
"be badly formatted: '%s' is not "
"an integer" % val)
# fill rest with zeros
palette = palette + [0] * (256 * 3 - len(palette))
self.userdata[COLOR_PALETTE_ATTRIBUTE] = palette
self.palette_img = PIL.Image.new("P", (1, 1))
self.palette_img.putpalette(palette)
# get labels if those were provided
if self.class_labels_file:
with open(self.class_labels_file) as f:
self.userdata['class_labels'] = f.read().splitlines()
def __init__(self, **kwargs):
"""
the parent __init__ method automatically populates this
instance with attributes from the form
"""
super(DataIngestion, self).__init__(**kwargs)
self.random_indices = None
if 'seed' not in self.userdata:
# choose random seed and add to userdata so it gets persisted
self.userdata['seed'] = random.randint(0, 1000)
if 'colormap_method' not in self.userdata:
self.userdata['colormap_method'] = 'label'
random.seed(self.userdata['seed'])
if self.userdata['colormap_method'] == "label":
# open first image in label folder to retrieve palette
# all label images must use the same palette - this is enforced
# during dataset creation
filename = self.make_image_list(self.label_folder)[0]
image = self.load_label(filename)
self.userdata[COLOR_PALETTE_ATTRIBUTE] = image.getpalette()
else:
# read colormap from file
with open(self.colormap_text_file) as f:
palette = []
lines = f.read().splitlines()
for line in lines:
for val in line.split():
try:
palette.append(int(val))
except:
raise ValueError("Your color map file seems to "
"be badly formatted: '%s' is not "
"an integer" % val)
# fill rest with zeros
palette = palette + [0] * (256 * 3 - len(palette))
self.userdata[COLOR_PALETTE_ATTRIBUTE] = palette
self.palette_img = PIL.Image.new("P", (1, 1))
self.palette_img.putpalette(palette)
# get labels if those were provided
if self.class_labels_file:
with open(self.class_labels_file) as f:
self.userdata['class_labels'] = f.read().splitlines()