Comments (6)
@Mahi-Mai thanks for bringing this up! I think it looks like the labels are possibly not being loaded. If you use the ippn leaf count dataset loader, it is by default looking for a file called Leaf_counts.csv
in the dataset folder which should have one image name, ground truth leaf count pair per line. Can you confirm the labels file is there?
from deepplantphenomics.
Thanks!
It's the file seen here: https://github.com/p2irc/deepplantphenomics/blob/master/deepplantphenomics/test_data/test_Ara2013_Canon/Leaf_counts.csv
My notebook is referencing the repo directly. I was able to import the library fine, so I don't see why I shouldn't be able to read this from my Notebook...
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Here are the results of pip freeze, if you're curious:
absl-py==0.4.0
aiohttp==1.0.5
alabaster==0.7.9
anaconda-clean==1.0
anaconda-client==1.5.1
anaconda-navigator==1.3.1
argcomplete==1.0.0
astor==0.7.1
astroid==1.4.7
astropy==1.2.1
async-timeout==1.0.0
Babel==2.3.4
backcall==0.1.0
backports.shutil-get-terminal-size==1.0.0
beautifulsoup4==4.5.1
bitarray==0.8.1
blaze==0.10.1
bleach==2.1.3
bokeh==0.12.2
boto==2.42.0
Bottleneck==1.1.0
cairocffi==0.7.2
cffi==1.7.0
chardet==2.3.0
chest==0.2.3
click==6.6
cloudpickle==0.2.1
clyent==1.2.2
colorama==0.3.7
conda==4.2.9
conda-build==2.0.4
configobj==5.0.6
contextlib2==0.5.3
cryptography==1.5
cycler==0.10.0
Cython==0.24.1
cytoolz==0.8.0
dask==0.11.0
datashape==0.5.2
decorator==4.3.0
dill==0.2.5
docutils==0.12
dynd==0.7.3.dev1
entrypoints==0.2.3
et-xmlfile==1.0.1
fastcache==1.0.2
filelock==2.0.6
Flask==0.11.1
Flask-Cors==2.1.2
gast==0.2.0
gevent==1.1.2
greenlet==0.4.10
grpcio==1.14.1
h5py==2.6.0
HeapDict==1.0.0
html5lib==1.0.1
idna==2.1
imagesize==0.7.1
ipykernel==4.8.2
ipython==6.3.1
ipython-genutils==0.2.0
ipywidgets==5.2.2
itsdangerous==0.24
jdcal==1.2
jedi==0.12.0
Jinja2==2.10
joblib==0.12.2
jsonschema==2.6.0
jupyter==1.0.0
jupyter-client==5.2.3
jupyter-console==5.0.0
jupyter-core==4.4.0
jupyterlab==0.32.0
jupyterlab-launcher==0.10.5
lazy-object-proxy==1.2.1
llvmlite==0.13.0
locket==0.2.0
lxml==3.6.4
Markdown==2.6.11
MarkupSafe==1.0
matplotlib==1.5.3
mistune==0.8.3
mpmath==0.19
multidict==2.1.2
multipledispatch==0.4.8
nb-anacondacloud==1.2.0
nb-conda==2.0.0
nb-conda-kernels==2.0.0
nbconvert==5.3.1
nbformat==4.4.0
nbpresent==3.0.2
networkx==1.11
nltk==3.2.1
nose==1.3.7
notebook==5.4.1
numba==0.28.1
numexpr==2.6.1
numpy==1.14.5
odo==0.5.0
opencv-python==3.2.0.6
openpyxl==2.3.2
pandas==0.23.4
pandocfilters==1.4.2
parso==0.2.0
partd==0.3.6
path.py==0.0.0
pathlib2==2.1.0
patsy==0.4.1
pep8==1.7.0
pexpect==4.5.0
pickleshare==0.7.4
Pillow==3.3.1
pkginfo==1.3.2
ply==3.9
prompt-toolkit==1.0.15
protobuf==3.6.1
psutil==4.3.1
psycopg2==2.6.2
ptyprocess==0.5.2
py==1.4.31
pyasn1==0.1.9
pycosat==0.6.1
pycparser==2.14
pycrypto==2.6.1
pycurl==7.43.0
pyflakes==1.3.0
Pygments==2.2.0
pylint==1.5.4
pymssql==2.1.3
pyOpenSSL==16.0.0
pyparsing==2.1.4
pytest==2.9.2
python-dateutil==2.7.2
pytz==2016.6.1
PyYAML==3.12
pyzmq==17.0.0
QtAwesome==0.3.3
qtconsole==4.2.1
QtPy==1.1.2
redis==2.10.5
requests==2.11.1
rope-py3k==0.9.4.post1
rpy2==2.8.3
ruamel-yaml===-VERSION
scikit-image==0.12.3
scikit-learn==0.18
scipy==0.19.1
seaborn==0.9.0
Send2Trash==1.5.0
simplegeneric==0.8.1
singledispatch==3.4.0.3
six==1.11.0
snowballstemmer==1.2.1
sockjs-tornado==1.0.3
Sphinx==1.4.6
sphinx-rtd-theme==0.1.9
spyder==3.0.0
SQLAlchemy==1.0.13
statsmodels==0.8.0
sympy==1.0
tables==3.2.3.1
tensorboard==1.10.0
tensorflow==1.10.0
termcolor==1.1.0
terminado==0.8.1
testpath==0.3.1
toolz==0.8.0
tornado==5.0.2
traitlets==4.3.2
unicodecsv==0.14.1
wcwidth==0.1.7
webencodings==0.5.1
Werkzeug==0.11.11
widgetsnbextension==1.2.6
wrapt==1.10.6
xlrd==1.0.0
XlsxWriter==0.9.3
xlwt==1.1.2
from deepplantphenomics.
I copied the test_data directory directly into mine and then edited the labels to match the filenames. (They didn't match.)
I redirected the model.load:
model.load_ippn_leaf_count_dataset_from_directory('./test_data/test_Ara2013_Canon')
When that didn't work I tried this:
model.load_multiple_labels_from_csv('./test_data/test_Ara2013_Canon/Leaf_counts.csv', id_column=0)
model.load_images_with_ids_from_directory('./test_data/test_Ara2013_Canon')
Each results in:
08:24PM: Total raw examples is 8
08:24PM: Parsing dataset...
But in the end model.begin_training() still fails with the same error as before.
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cc @NHiggs
from deepplantphenomics.
@Mahi-Mai thanks for pointing this out to us. The latest version of master should be working correctly for you now.
Let us know of any further issues.
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Related Issues (12)
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