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jubbens avatar jubbens commented on June 26, 2024

@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?

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Mahi-Mai avatar Mahi-Mai commented on June 26, 2024

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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Mahi-Mai avatar Mahi-Mai commented on June 26, 2024

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

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Mahi-Mai avatar Mahi-Mai commented on June 26, 2024

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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jubbens avatar jubbens commented on June 26, 2024

cc @NHiggs

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nicohiggs avatar nicohiggs commented on June 26, 2024

@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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