Closed xwf12345678 closed 2 years ago
WAMAWAMA
commented
2 years ago 1）如果你用的是我们提供的数据（比如DDTI数据），那么这个就是imgaug版本问题，多试几个imgaug库的版本即可~ 2）或者改一下代码，把images_aug = seq_det.augment_images(imgs) 这里的imgs提前用 np.expand_dims(imgs, 0)扩增一下维度，扩增后再把images_aug 的第一个维度np.squeeze掉就可以了👍
xwf12345678
commented
2 years ago 那请问你们当时所使用的imgaug版本是多少呢？
WAMAWAMA
commented
2 years ago 当时的找不到了，不过现在用的如下👇 Package Version
alabaster 0.7.12
anaconda-client 1.7.2
anaconda-navigator 1.9.7
anaconda-project 0.8.3
antspyx 0.2.7
asn1crypto 1.0.1
astroid 2.3.1
astropy 3.2.2
atomicwrites 1.3.0
attrs 19.2.0
Babel 2.7.0
backcall 0.1.0
backports.functools-lru-cache 1.5
backports.os 0.1.1
backports.shutil-get-terminal-size 1.0.0
backports.tempfile 1.0
backports.weakref 1.0.post1
batchgenerators 0.21
beautifulsoup4 4.8.0
bitarray 1.0.1
bkcharts 0.2
bleach 3.1.0
bokeh 1.3.4
boto 2.49.0
Bottleneck 1.2.1
certifi 2019.9.11
cffi 1.12.3
chardet 3.0.4
chart-studio 1.1.0
Click 7.0
cloudpickle 1.2.2
clyent 1.2.2
colorama 0.4.1
conda 4.9.0
conda-build 3.18.9
conda-package-handling 1.6.0
conda-verify 3.4.2
contextlib2 0.6.0
cryptography 2.7
cycler 0.10.0
Cython 0.29.13
cytoolz 0.10.0
dask 2.5.2
decorator 4.4.0
defusedxml 0.6.0
dicom2nifti 2.3.0
distributed 2.5.2
docutils 0.15.2
efficientnet-pytorch 0.6.3
einops 0.3.0
entrypoints 0.3
et-xmlfile 1.0.1
fastcache 1.1.0
filelock 3.0.12
Flask 1.1.1
fsspec 0.5.2
future 0.17.1
gevent 1.4.0
glob2 0.7
gmpy2 2.0.8
greenlet 0.4.15
h5py 2.9.0
HeapDict 1.0.1
html5lib 1.0.1
idna 2.8
imageio 2.6.0
imagesize 1.1.0
imgaug 0.4.0
importlib-metadata 0.23
ipykernel 5.1.2
ipython 7.8.0
ipython-genutils 0.2.0
ipywidgets 7.5.1
isort 4.3.21
itsdangerous 1.1.0
jdcal 1.4.1
jedi 0.15.1
jeepney 0.4.1
Jinja2 2.10.3
joblib 0.13.2
json5 0.8.5
jsonschema 3.0.2
jupyter 1.0.0
jupyter-client 5.3.3
jupyter-console 6.0.0
jupyter-core 4.5.0
jupyterlab 1.1.4
jupyterlab-server 1.0.6
keyring 18.0.0
kiwisolver 1.1.0
lazy-object-proxy 1.4.2
libarchive-c 2.8
libtiff 0.4.2
lief 0.9.0
linecache2 1.0.0
llvmlite 0.29.0
locket 0.2.0
lxml 4.4.1
Mako 1.1.4
Markdown 3.3.4
MarkupSafe 1.1.1
matplotlib 3.1.1
mccabe 0.6.1
medcam 0.1.6
MedPy 0.4.0
mistune 0.8.4
mkl-fft 1.0.14
mkl-random 1.1.0
mkl-service 2.3.0
mock 3.0.5
more-itertools 7.2.0
mpmath 1.1.0
msgpack 0.6.1
multipledispatch 0.6.0
munch 2.5.0
navigator-updater 0.2.1
nbconvert 5.6.0
nbformat 4.4.0
networkx 2.3
nibabel 3.2.1
nltk 3.4.5
nnunet 1.6.6
nose 1.3.7
notebook 6.0.1
numba 0.45.1
numexpr 2.7.0
numpy 1.21.2
numpydoc 0.9.1
olefile 0.46
opencv-python 4.0.0.21
openpyxl 3.0.0
packaging 19.2
pandas 0.25.1
pandocfilters 1.4.2
parso 0.5.1
partd 1.0.0
path.py 12.0.1
pathlib2 2.3.5
patsy 0.5.1
pep8 1.7.1
pexpect 4.7.0
pickleshare 0.7.5
Pillow 8.3.1
pip 19.2.3
pkginfo 1.5.0.1
plotly 4.14.3
pluggy 0.13.0
ply 3.11
pretrainedmodels 0.7.4
prettytable 2.4.0
prometheus-client 0.7.1
prompt-toolkit 2.0.10
protobuf 3.15.6
psutil 5.6.3
ptyprocess 0.6.0
py 1.8.0
pycodestyle 2.5.0
pycosat 0.6.3
pycparser 2.19
pycrypto 2.6.1
pycurl 7.43.0.3
pydicom 2.2.1
pyflakes 2.1.1
Pygments 2.4.2
pylint 2.4.2
pymrmr 0.1.11
pyodbc 4.0.27
pyOpenSSL 19.0.0
pyparsing 2.4.2
pyrsistent 0.15.4
PySide2 5.15.2
PySocks 1.7.1
pytest 5.2.1
pytest-arraydiff 0.3
pytest-astropy 0.5.0
pytest-doctestplus 0.4.0
pytest-openfiles 0.4.0
pytest-remotedata 0.3.2
python-dateutil 2.8.0
pytz 2019.3
PyWavelets 1.0.3
PyYAML 5.1.2
pyzmq 18.1.0
QtAwesome 0.6.0
qtconsole 4.5.5
QtPy 1.9.0
requests 2.22.0
retrying 1.3.3
rope 0.14.0
ruamel-yaml 0.15.46
scikit-image 0.15.0
scikit-learn 0.23.0
scipy 1.3.1
seaborn 0.9.0
SecretStorage 3.1.1
segmentation-models-pytorch 0.1.2
Send2Trash 1.5.0
setuptools 41.4.0
Shapely 1.7.1
shiboken2 5.15.2
simplegeneric 0.8.1
SimpleITK 1.2.4
singledispatch 3.4.0.3
six 1.12.0
sklearn 0.0
snowballstemmer 2.0.0
sortedcollections 1.1.2
sortedcontainers 2.1.0
soupsieve 1.9.3
Sphinx 2.2.0
sphinxcontrib-applehelp 1.0.1
sphinxcontrib-devhelp 1.0.1
sphinxcontrib-htmlhelp 1.0.2
sphinxcontrib-jsmath 1.0.1
sphinxcontrib-qthelp 1.0.2
sphinxcontrib-serializinghtml 1.1.3
sphinxcontrib-websupport 1.1.2
spyder 3.3.6
spyder-kernels 0.5.2
SQLAlchemy 1.3.9
statsmodels 0.10.1
sympy 1.4
tables 3.5.2
tblib 1.4.0
tensorboardX 2.1
terminado 0.8.2
testpath 0.4.2
threadpoolctl 2.1.0
tifffile 2021.8.8
timm 0.2.1
toolz 0.10.0
torch 1.6.0+cu101
torchvision 0.7.0+cu101
tornado 6.0.3
tqdm 4.36.1
traceback2 1.4.0
traitlets 4.3.3
ttach 0.0.3
unicodecsv 0.14.1
unittest2 1.1.0
urllib3 1.24.2
wcwidth 0.1.7
webcolors 1.11.1
webencodings 0.5.1
Werkzeug 0.16.0
wheel 0.33.6
widgetsnbextension 3.5.1
wrapt 1.11.2
wurlitzer 1.0.3
xlrd 1.2.0
XlsxWriter 1.2.1
xlwt 1.3.0
zict 1.0.0
zipp 0.6.0
File "/content/drive/Shareddrives/wufeixie111@gmail.com/TNSCUI2020-Seg-Rank1st/step2to4_train_validate_inference/loader/data_loader.py", line 281, in getitem [image, GT] = data_aug(image, GT) File "/content/drive/Shareddrives/wufeixie111@gmail.com/TNSCUI2020-Seg-Rank1st/step2to4_train_validate_inference/loader/img_mask_aug.py", line 117, in data_aug images_aug = seq_det.augment_images(imgs) # 进行增强 File "/usr/local/lib/python3.7/dist-packages/imgaug/augmenters/meta.py", line 542, in augment_images "got shape %s." % (images.shape,)) File "/usr/local/lib/python3.7/dist-packages/imgaug/imgaug.py", line 1869, in do_assert raise AssertionError(str(message)) AssertionError: Expected 3d/4d array of form (N, height, width) or (N, height, width, channels), got shape (256, 256).