def resolve_color(channel):
color = colors.get(channel, None)
if color is None or isinstance(color, str):
return cvcolor.map(color)
else:
if len(color) != 3 or np.array(color).min() < 0 or np.array(color).max() > 1:
raise ValueError(
'Color for channel "{}" should be 3 item list-like with values in [0, 1] not "{}"'
.format(channel, color)
)
return color
def _load_montage_data():
from skimage.transform import resize
path = cytokit_io.get_montage_image_path(cfg.region_index,
cfg.montage_name)
path = osp.join(cfg.exp_data_dir, path)
img, meta = cytokit_io.read_tile(path, return_metadata=True)
# Select cycle and z plane
img = img[cfg.montage_cycle, cfg.montage_z]
labels = list(meta['structured_labels'][cfg.montage_cycle, cfg.montage_z])
############################
# Montage Display Properties
############################
channel_filter = cfg.montage_channel_names
if channel_filter is not None:
# Validate that all provided channel names exist
for c in channel_filter:
if c not in labels:
raise ValueError(
'Configured montage channel name "{}" does not exist in montage image '
'(available channels = {}); Fix or remove this channel name from the (comma-separated) environment '
'variable "{}" and run again'.format(
c, labels, ENV_APP_MONTAGE_CHANNEL_NAMES))
# Subset both the image and the labels to the channels provided (make sure order of arrays matches
# order of given channels -- which then matches to other montage options like color/range)
img = img[np.array([labels.index(c) for c in channel_filter])]
labels = channel_filter
ranges = cfg.montage_channel_ranges
colors = cfg.montage_channel_colors
# Map string color names to rgb multipliers
if colors is not None:
colors = [color.map(c) for c in colors]
####################
# Montage Resampling
####################
logger.info('Loaded montage image with shape = %s, dtype = %s', img.shape,
img.dtype)
if img.dtype != np.uint8 and img.dtype != np.uint16:
raise ValueError(
'Only 8 or 16 bit images are supported (image type = {})'.format(
img.dtype))
# Resize the montage image to something much smaller (resize function expects channels last
# and preserves them if not specified in target shape)
img = np.moveaxis(img, 0, -1)
img = resize(img,
cfg.montage_target_shape,
order=0,
mode='constant',
anti_aliasing=False,
preserve_range=True).astype(img.dtype)
img = np.moveaxis(img, -1, 0)
# Image is now (C, H, W)
db.put('images', 'montage', img)
db.put('channels', 'montage', labels)
db.put('colors', 'montage', colors)
db.put('ranges', 'montage', ranges)
def handle_display_settings_update(channel_ranges, channel_colors):
data.db.put('app', 'tile_channel_ranges', channel_ranges)
data.db.put('app', 'tile_channel_colors', channel_colors)
ac['processor']['tile'].ranges = channel_ranges
ac['processor']['tile'].colors = [color.map(c) for c in channel_colors]