def caller(inputs, inputs_labels, output, functions, params):
make_dirs(output)
# Make cells. cells are a list of regionproperties or subclasses.
logger.info('Postprocess.\tcollecting cells...')
store = []
for frame, (path, pathl) in enumerate(zip(inputs, inputs_labels)):
img, labels = imread(path), lbread(pathl)
cells = regionprops(labels, img)
cells = [Cell(cell) for cell in cells]
for cell in cells:
cell.frame = frame
if frame > 0:
all_labels = [i.label for i in store[frame - 1]]
if cell.label in all_labels:
store[frame - 1][all_labels.index(cell.label)].nxt = cell
store.append(cells)
cells = [i for j in store for i in j]
# Each function receives cells (regionprops) and finally return labels generated by cells.label
for function, param in zip(functions, params):
logger.info('\trunning {0}'.format(function))
func = getattr(postprocess_operation, function)
cells = func(cells, **param)
logger.info('\tsaving images...')
for frame, (path, pathl) in enumerate(zip(inputs, inputs_labels)):
labels = cells2labels(cells, frame, lbread(pathl))
imsave(labels, output, path, dtype=np.int16)
def caller(inputs, inputs_labels, output, functions, params):
make_dirs(output)
inputs = inputs[FRAME_REVTRACK:0:-1] + inputs
inputs_labels = inputs_labels[FRAME_REVTRACK:0:-1] + inputs_labels
img0, labels0 = imread(inputs[0]), lbread(inputs_labels[0]).astype(
np.int16)
labels0 = neg2poslabels(labels0)
imsave(labels0, output, basename(inputs[0]), dtype=np.int16)
for holder.frame, (path,
pathl) in enumerate(zip(inputs[1:], inputs_labels[1:])):
img1, labels1 = imread(path), lbread(pathl)
labels1 = -labels1
for fnum, (function, param) in enumerate(zip(functions, params)):
func = getattr(track_operation, function)
if not (labels1 < 0).any():
continue
labels0, labels1 = func(img0, img1, labels0, -labels1, **param)
logger.debug('\t{0} with {1}: {2}'.format(
function, param, len(set(labels1[labels1 < 0]))))
logger.info("\tframe {0}: {1} objects linked and {2} unlinked.".format(
holder.frame, len(set(labels1[labels1 > 0])),
len(set(labels1[labels1 < 0]))))
labels0 = neg2poslabels(labels1)
img0 = img1
imsave(labels0, output, path, dtype=np.int16)
def caller(inputs, output, functions, params):
holder.inputs = inputs
make_dirs(output)
logger.info("Functions {0} for {1} images.".format(functions, len(inputs)))
for holder.frame, holder.path in enumerate(inputs):
img = imread(holder.path)
for function, param in zip(functions, params):
func = getattr(preprocess_operation, function)
img = func(img, **param)
imsave(img, output, holder.path)
logger.info("\tframe {0} done.".format(holder.frame))
def caller(inputs, output, functions, params):
make_dirs(output)
logger.info("Functions {0} for {1} images.".format(functions, len(inputs)))
for holder.frame, path in enumerate(inputs):
img = imread(path)
for function, param in zip(functions, params):
func = getattr(segment_operation, function)
img = func(img, **param)
if isinstance(path, list) or isinstance(path, tuple):
path = path[0]
labels = clean_labels(img, radius)
imsave(labels, output, path, dtype=np.int16)
logger.info("\tframe {0}: {1} objects segmented.".format(
holder.frame, len(np.unique(labels))))
def caller(inputs, inputs_labels, output, functions, params):
make_dirs(output)
logger.info("Functions {0} for {1} images.".format(functions, len(inputs)))
img = None
for holder.frame, (path,
pathl) in enumerate(izip_longest(inputs,
inputs_labels)):
if path is not None:
img = imread(path)
labels0 = lbread(pathl)
for function, param in zip(functions, params):
func = getattr(subdetect_operation, function)
if img is not None:
labels = func(labels0, img, **param)
else:
labels = func(labels0, **param)
imsave(labels, output, pathl, dtype=np.int16)
logger.info("\tframe {0} done.".format(holder.frame))
