def callback():
print("updating")
if prev_threshold != threshold.value:
new_segmented_image_stack = segmentation.segment_stack(
channel_file, "fixed", threshold=threshold.value)
new_segmented_image_stack = new_segmented_image_stack.labelled_image > 1
segmented_image_source.data = dict(
image=[new_segmented_image_stack[layer.value]])
else:
segmented_image_source.data = dict(
image=[segmented_image_stack[layer.value]])
nominal_image_source.data = dict(image=[nominal_image_stack[layer.value]])
def callback():
print("updating")
print(prev_c, c.value, prev_window_size,layer.value)
if prev_c != c.value or prev_window_size != window_size.value:
new_segmented_image_stack = segmentation.segment_stack(
channel_file,
"autolocal",
window_size=window_size.value,
c_factor=c.value,
min_vox_size=min_voxel_size.value,
max_vox_size=max_voxel_size.value
)
new_segmented_image_stack = new_segmented_image_stack.labelled_image > 1
segmented_image_source.data = dict(image=[new_segmented_image_stack[layer.value]])
else:
segmented_image_source.data = dict(image=[segmented_image_stack[layer.value]])
nominal_image_source.data = dict(image=[nominal_image_stack[layer.value]])
def server_run_segment(config: dict):
input_dir = config["input_dir"]
output_dir = config["output_dir"]
file_pattern = config["files"]
threshold_method = config["threshold_method"]
threshold_params = config["threshold_params"]
utils.check_dir_exists(input_dir)
utils.check_dir_exists(output_dir)
_save_config(config)
files_to_segment = glob.glob(f"{input_dir}/{file_pattern}")
logger.info(f"{files_to_segment}")
for i, file_name in enumerate(files_to_segment):
logger.info(f"{i+1}/{len(files_to_segment)}")
channel_file = File.from_tiff(file_name)
segmented_file = segmentation.segment_stack(channel_file,
threshold_method, 3, 90000,
**threshold_params)
segmented_file.save_to_tiff(output_dir)
from lib import File, segmentation, image_adjustments
def reverse_palette(palette):
list_palette = [x for x in palette]
list_palette.reverse()
return list_palette
file_name = sys.argv[1]
RGreens7 = reverse_palette(Greens7)
ROrRd3 = reverse_palette(OrRd3)
channel_file = File.from_tiff(file_name)
segmented_image_stack = segmentation.segment_stack(
channel_file, "fixed", threshold=channel_file.image.mean())
segmented_image_stack = segmented_image_stack.labelled_image > 1
nominal_image_stack = image_adjustments.rescale_intensity(channel_file)
main_fig = figure(plot_height=500,
plot_width=500,
title="Segmentation",
sizing_mode="scale_both")
print((nominal_image_stack.max()))
layer = Slider(start=0,
end=len(nominal_image_stack),
value=0,
step=1,
title="z layer")
threshold = Slider(start=0,
def reverse_palette(palette):
list_palette = [x for x in palette]
list_palette.reverse()
return list_palette
file_name = sys.argv[1]
RGreens7 = reverse_palette(Greens7)
ROrRd3 = reverse_palette(OrRd3)
channel_file = File.from_tiff(file_name)
segmented_image_stack = segmentation.segment_stack(
channel_file,
"autolocal",
window_size=1,
c_factor=1,
min_vox_size=3,
max_vox_size=9999
)
segmented_image_stack = segmented_image_stack.labelled_image > 1
nominal_image_stack = image_adjustments.rescale_intensity(channel_file)
main_fig = figure(
plot_height=500,
plot_width=500,
title="Segmentation",
sizing_mode="scale_both"
)
layer = Slider(start=0, end=len(nominal_image_stack), value=0, step=1, title="z layer")