andreped / livermask Goto Github PK

Traceback (most recent call last):
File "C:\Users\Cyanb\anaconda3\envs\spade\lib\runpy.py", line 193, in _run_module_as_main
"main", mod_spec)
File "C:\Users\Cyanb\anaconda3\envs\spade\lib\runpy.py", line 85, in _run_code
exec(code, run_globals)
File "C:\Users\Cyanb\anaconda3\envs\spade\lib\site-packages\livermask\livermask.py", line 116, in
main()
File "C:\Users\Cyanb\anaconda3\envs\spade\lib\site-packages\livermask\livermask.py", line 112, in main
func(*vars(ret).values())
File "C:\Users\Cyanb\anaconda3\envs\spade\lib\site-packages\livermask\livermask.py", line 40, in func
get_model(name)
File "C:\Users\Cyanb\anaconda3\envs\spade\lib\site-packages\livermask\utils\utils.py", line 10, in get_model
gdown.cached_download(url, output, md5=md5) #, postprocess=gdown.extractall)
File "C:\Users\Cyanb\anaconda3\envs\spade\lib\site-packages\gdown\cached_download.py", line 123, in cached_download
download(url, temp_path, quiet=quiet, proxy=proxy, speed=speed)
File "C:\Users\Cyanb\anaconda3\envs\spade\lib\site-packages\gdown\download.py", line 114, in download
res = sess.get(url, headers=headers, stream=True)
File "C:\Users\Cyanb\anaconda3\envs\spade\lib\site-packages\requests\sessions.py", line 555, in get
return self.request('GET', url, **kwargs)
File "C:\Users\Cyanb\anaconda3\envs\spade\lib\site-packages\requests\sessions.py", line 528, in request
prep = self.prepare_request(req)
File "C:\Users\Cyanb\anaconda3\envs\spade\lib\site-packages\requests\sessions.py", line 466, in prepare_request
hooks=merge_hooks(request.hooks, self.hooks),
File "C:\Users\Cyanb\anaconda3\envs\spade\lib\site-packages\requests\models.py", line 316, in prepare
self.prepare_url(url, params)
File "C:\Users\Cyanb\anaconda3\envs\spade\lib\site-packages\requests\models.py", line 390, in prepare_url
raise MissingSchema(error)
requests.exceptions.MissingSchema: Invalid URL '': No schema supplied. Perhaps you meant http://?

Did anyone have the same issue as me?

Cached Downloading: E:/Task2311/livermask-main/livermask/utils/model-hepatic_vessel.npz
Traceback (most recent call last):
File "C:\Users\10495.conda\envs\v6\lib\site-packages\urllib3\connection.py", line 170, in _new_conn
(self._dns_host, self.port), self.timeout, **extra_kw
File "C:\Users\10495.conda\envs\v6\lib\site-packages\urllib3\util\connection.py", line 96, in create_connection
raise err
File "C:\Users\10495.conda\envs\v6\lib\site-packages\urllib3\util\connection.py", line 86, in create_connection
sock.connect(sa)
TimeoutError: [WinError 10060] 由于连接方在一段时间后没有正确答复或连接的主机没有反应，连接尝试失败。

liver is ok,but there are some errores in liver vessels program when cached downloading model-hepatic_vessel.npz

Recent CI builds failed as it seems like gdown was unable to download the models from Google Drive.

I have checked the drive, and the models are there and available.

Hence, probably something wrong with the recent version of gdown. Should try to downgrade gdown and test again.

Hello Andre, and thank you very much for sharing your code!
I have been trying to install and run your code on my PC, but unfortunately nothing happens after the first TQDM progress bar (no log information are shown, and even if everything seems to work fine, no segmentation is produced).

I have a doubt:

Line 73 of "livermask.py"
if not curr.endswith(".ini"):
continue

Could this be a typo (".ini" instead of ".nii")?
Maybe my files are all skipped and that's why I don't get a segmentation nor a warning.

Many thanks!
Silvia

I get the following errors when installing livermask wih "pip install git+https://github.com/andreped/livermask.git":
Downloading llvmlite-0.36.0-cp38-cp38-win_amd64.whl (16.0 MB)
|███████████████████████ | 11.5 MB ... ERROR: Exception:
Traceback (most recent call last):
File "c:\program files\python38\lib\site-packages\pip_vendor\urllib3\response.py", line 438, in _error_catcher
yield
File "c:\program files\python38\lib\site-packages\pip_vendor\urllib3\response.py", line 519, in read
data = self._fp.read(amt) if not fp_closed else b""
File "c:\program files\python38\lib\site-packages\pip_vendor\cachecontrol\filewrapper.py", line 62, in read
data = self.__fp.read(amt)
File "c:\program files\python38\lib\http\client.py", line 455, in read
n = self.readinto(b)
File "c:\program files\python38\lib\http\client.py", line 499, in readinto
n = self.fp.readinto(b)
File "c:\program files\python38\lib\socket.py", line 669, in readinto
return self._sock.recv_into(b)
File "c:\program files\python38\lib\ssl.py", line 1241, in recv_into
return self.read(nbytes, buffer)
File "c:\program files\python38\lib\ssl.py", line 1099, in read
return self._sslobj.read(len, buffer)
socket.timeout: The read operation timed out

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "c:\program files\python38\lib\site-packages\pip_internal\cli\base_command.py", line 180, in _main
status = self.run(options, args)
File "c:\program files\python38\lib\site-packages\pip_internal\cli\req_command.py", line 204, in wrapper
return func(self, options, args)
File "c:\program files\python38\lib\site-packages\pip_internal\commands\install.py", line 318, in run
requirement_set = resolver.resolve(
File "c:\program files\python38\lib\site-packages\pip_internal\resolution\resolvelib\resolver.py", line 127, in resolve
result = self._result = resolver.resolve(
File "c:\program files\python38\lib\site-packages\pip_vendor\resolvelib\resolvers.py", line 473, in resolve
state = resolution.resolve(requirements, max_rounds=max_rounds)
File "c:\program files\python38\lib\site-packages\pip_vendor\resolvelib\resolvers.py", line 367, in resolve
failure_causes = self._attempt_to_pin_criterion(name)
File "c:\program files\python38\lib\site-packages\pip_vendor\resolvelib\resolvers.py", line 213, in _attempt_to_pin_criterion
criteria = self._get_criteria_to_update(candidate)
File "c:\program files\python38\lib\site-packages\pip_vendor\resolvelib\resolvers.py", line 203, in _get_criteria_to_update
name, crit = self._merge_into_criterion(r, parent=candidate)
File "c:\program files\python38\lib\site-packages\pip_vendor\resolvelib\resolvers.py", line 172, in _merge_into_criterion
if not criterion.candidates:
File "c:\program files\python38\lib\site-packages\pip_vendor\resolvelib\structs.py", line 139, in bool
return bool(self._sequence)
File "c:\program files\python38\lib\site-packages\pip_internal\resolution\resolvelib\found_candidates.py", line 143, in bool
return any(self)
File "c:\program files\python38\lib\site-packages\pip_internal\resolution\resolvelib\found_candidates.py", line 129, in
return (c for c in iterator if id(c) not in self._incompatible_ids)
File "c:\program files\python38\lib\site-packages\pip_internal\resolution\resolvelib\found_candidates.py", line 33, in _iter_built
candidate = func()
File "c:\program files\python38\lib\site-packages\pip_internal\resolution\resolvelib\factory.py", line 200, in _make_candidate_from_link
self._link_candidate_cache[link] = LinkCandidate(
File "c:\program files\python38\lib\site-packages\pip_internal\resolution\resolvelib\candidates.py", line 306, in init
super().init(
File "c:\program files\python38\lib\site-packages\pip_internal\resolution\resolvelib\candidates.py", line 151, in init
self.dist = self._prepare()
File "c:\program files\python38\lib\site-packages\pip_internal\resolution\resolvelib\candidates.py", line 234, in _prepare
dist = self._prepare_distribution()
File "c:\program files\python38\lib\site-packages\pip_internal\resolution\resolvelib\candidates.py", line 317, in _prepare_distribution
return self._factory.preparer.prepare_linked_requirement(
File "c:\program files\python38\lib\site-packages\pip_internal\operations\prepare.py", line 508, in prepare_linked_requirement
return self._prepare_linked_requirement(req, parallel_builds)
File "c:\program files\python38\lib\site-packages\pip_internal\operations\prepare.py", line 550, in _prepare_linked_requirement
local_file = unpack_url(
File "c:\program files\python38\lib\site-packages\pip_internal\operations\prepare.py", line 239, in unpack_url
file = get_http_url(
File "c:\program files\python38\lib\site-packages\pip_internal\operations\prepare.py", line 102, in get_http_url
from_path, content_type = download(link, temp_dir.path)
File "c:\program files\python38\lib\site-packages\pip_internal\network\download.py", line 157, in call
for chunk in chunks:
File "c:\program files\python38\lib\site-packages\pip_internal\cli\progress_bars.py", line 152, in iter
for x in it:
File "c:\program files\python38\lib\site-packages\pip_internal\network\utils.py", line 62, in response_chunks
for chunk in response.raw.stream(
File "c:\program files\python38\lib\site-packages\pip_vendor\urllib3\response.py", line 576, in stream
data = self.read(amt=amt, decode_content=decode_content)
File "c:\program files\python38\lib\site-packages\pip_vendor\urllib3\response.py", line 541, in read
raise IncompleteRead(self._fp_bytes_read, self.length_remaining)
File "c:\program files\python38\lib\contextlib.py", line 131, in exit
self.gen.throw(type, value, traceback)
File "c:\program files\python38\lib\site-packages\pip_vendor\urllib3\response.py", line 443, in _error_catcher
raise ReadTimeoutError(self._pool, None, "Read timed out.")
pip._vendor.urllib3.exceptions.ReadTimeoutError: HTTPSConnectionPool(host='files.pythonhosted.org', port=443): Read timed out.

@andreped can you help?

Hello again Andre,
I'd like to fine tune your network on MRIs - to see if I can get any good result on liver segmentation on MRI instead of CT.

Can I ask you how the data generator should be organized?
In particular, I am having some issues with input shape of the image and of the mask.
I can see the input image for prediction should be like (1,1,512,512,1), so I guess it's (batchsize, 1 (slice), 512,512, 1 channel)?
It would be super if you could share an example of how the input data is passed to the net.

Thank you very much and have a good weekend,
Silvia

When running livermask on a server solution, I suddenly got this issue, which seems to be sporadic:

> requests.exceptions.HTTPError: 503 Server Error: Egress is over the account limit.

It seems to fail when downloading the parenchyma model, which is downloaded from the GitHub Release tag.

Might be that we have to setup our own self-hosted server solution for these models instead.

I apologize in advance for a possibly stupid question. But what does the --verbose flag do? I used it but didn't understand what changed

When installing the latest version of livermask on macOS 12:

pip install livermask==1.4.0

from the installation verbose we observe:

> ERROR: livermask 1.4.0 has requirement importlib-metadata==4.8.1, but you'll have importlib-metadata 5.2.0 which is incompatible.
> ERROR: livermask 1.4.0 has requirement Werkzeug==2.0.1, but you'll have werkzeug 2.2.2 which is incompatible.

It still manages to install, but this is suboptimal. Should find a way to avoid this from happening.

Seems like the model can no longer be downloaded. I might have deleted it when accidentally when cleaning my google drive.

Hello,

I want to use livermask to segment CT images as a part of a project through my organization. We are really excited to use your tool because it will automate a lot of the segmentation we would have otherwise had to do. However, I stumbled on the following error:
RuntimeError: module compiled against API version 0xe but this version of numpy is 0xd
RuntimeError: module compiled against API version 0xe but this version of numpy is 0xd
Traceback (most recent call last):
File "/Users/giulia/.conda/envs/liver/bin/livermask", line 33, in
sys.exit(load_entry_point('livermask==1.3.0', 'console_scripts', 'livermask')())
File "/Users/giulia/.conda/envs/liver/bin/livermask", line 25, in importlib_load_entry_point
return next(matches).load()
File "/Users/giulia/.conda/envs/liver/lib/python3.8/importlib/metadata.py", line 77, in load
module = import_module(match.group('module'))
File "/Users/giulia/.conda/envs/liver/lib/python3.8/importlib/init.py", line 127, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
File "", line 1014, in _gcd_import
File "", line 991, in _find_and_load
File "", line 975, in _find_and_load_unlocked
File "", line 671, in _load_unlocked
File "", line 783, in exec_module
File "", line 219, in _call_with_frames_removed
File "/Users/giulia/.conda/envs/liver/lib/python3.8/site-packages/livermask-1.3.0-py3.8.egg/livermask/livermask.py", line 6, in
from scipy.ndimage import zoom
File "/Users/giulia/.conda/envs/liver/lib/python3.8/site-packages/scipy-1.5.4-py3.8-macosx-11.0-arm64.egg/scipy/ndimage/init.py", line 151, in
from .filters import *
File "/Users/giulia/.conda/envs/liver/lib/python3.8/site-packages/scipy-1.5.4-py3.8-macosx-11.0-arm64.egg/scipy/ndimage/filters.py", line 37, in
from . import _nd_image
ImportError: numpy.core.multiarray failed to import

I have installed numpy==1.19.5 as requested by livermask and I work on a Macos M1 machine.
Could you please help me?

Describe the solution you'd like
Would just like a section in the ReadMe about how well this model performs in segmenting liver parenchyma and vessels. Will be useful in integrating it into scientific papers.