Hi,
I am trying to implement "Automate Road Surface Investigation Using Deep Learning" sample procedures in my pc. but while trying to execute the code
data = prepare_data(data_path, batch_size=4, chip_size=500, seed=42, dataset_type='PASCAL_VOC_rectangles')
I get the following error.
I have checked the conda list it. the environment has the necessary packages it needs to be there. I am attaching the conda list as well. Can someone please help me on what am I doing wrong?
(arcgis-fastai) C:\Users\username\AppData\Local\ESRI\conda\envs\arcgis-fastai>conda
list
# packages in environment at C:\Users\username\AppData\Local\ESRI\conda\envs\arcgis
-fastai:
#
arcgis 1.7.1 py36_969 esri
arcgispro 2.4 0 esri
asn1crypto 1.3.0 py36_0
atomicwrites 1.3.0 py36_1
attrs 19.3.0 py_0
backcall 0.1.0 py36_0
beautifulsoup4 4.8.2 py36_0
blas 1.0 mkl
bleach 3.1.0 py_0
bottleneck 1.3.1 py36h8c2d366_0
ca-certificates 2020.1.1 0
certifi 2019.11.28 py36_0
cffi 1.13.2 py36h7a1dbc1_0
cftime 1.0.0b1 py36h452e1ab_0
chardet 3.0.4 py36_1003
colorama 0.4.3 py_0
cryptography 2.8 py36h7a1dbc1_0
cudatoolkit 10.0.130 0
cycler 0.10.0 py36h009560c_0
cymem 2.0.2 py36h6538335_0 fastai
cython-blis 0.2.4 py36hfa6e2cd_1 fastai
dataclasses 0.6 py_0 fastai
decorator 4.4.1 py_0
defusedxml 0.6.0 py_0
despatch 0.1.0 py36_0 esri
entrypoints 0.3 py36_0
et_xmlfile 1.0.1 py36h3d2d736_0
fastai 1.0.54 py36_0 esri
fastcache 1.1.0 py36he774522_0
fastprogress 0.2.2 py_0 fastai
freetype 2.9.1 vc14_0 [vc14] esri
future 0.18.2 py36_0
gdal 2.3.3 arcgispro_11 [arcgispro] esri
h5py 2.9.0 py36_arcgispro_0 [arcgispro] esri
html5lib 1.0.1 py_0
icc_rt 2019.0.4 arcgispro_0 [arcgispro] esri
idna 2.8 py36_0
imageio 2.6.1 py36_0
importlib_metadata 1.4.0 py36_0
intel-openmp 2019.4 arcgispro_245 [arcgispro] esri
ipykernel 5.1.4 py36h39e3cac_0
ipython 7.11.1 py36h39e3cac_0
ipython_genutils 0.2.0 py36_0
ipywidgets 7.5.1 py_0
jdcal 1.4.1 py_0
jedi 0.16.0 py36_0
jinja2 2.10.3 py_0
jpeg 9b hb83a4c4_2
json5 0.8.5 py_0
jsonschema 3.2.0 py36_0
jupyter_client 5.3.4 py36_0
jupyter_console 6.1.0 py_0
jupyter_core 4.6.1 py36_0
jupyterlab 1.2.5 pyhf63ae98_0
jupyterlab_server 1.0.6 py_0
keyring 21.1.0 py36_0
kiwisolver 1.1.0 py36ha925a31_0
libpng 1.6.37 h2a8f88b_0
libsodium 1.0.16 h9d3ae62_0
libtiff 4.1.0 h56a325e_0
m2w64-gcc-libgfortran 5.3.0 6
m2w64-gcc-libs 5.3.0 7
m2w64-gcc-libs-core 5.3.0 7
m2w64-gmp 6.1.0 2
m2w64-libwinpthread-git 5.0.0.4634.697f757 2
markupsafe 1.1.1 py36he774522_0
matplotlib 3.0.3 py36_0e [arcgispro] esri
mistune 0.8.4 py36he774522_0
mkl 2019.3 arcgispro_203 [arcgispro] esri
mkl_fft 1.0.12 py36h14836fe_0
mkl_random 1.0.2 py36h343c172_0
more-itertools 8.0.2 py_0
mpmath 1.1.0 py36_0
msys2-conda-epoch 20160418 1
murmurhash 1.0.2 py36h33f27b4_0
nb_conda 2.2.1 py36_0
nb_conda_kernels 2.2.2 py36_0
nbconvert 5.6.1 py36_0
nbformat 5.0.4 py_0
netcdf4 1.5.0.1 py36_arcgispro_1 [arcgispro] esri
networkx 2.4 py_0
ninja 1.9.0 py36h74a9793_0
nose 1.3.7 py36_2
notebook 6.0.3 py36_0
numexpr 2.6.9 py36hdce8814_0
numpy 1.16.2 py36h19fb1c0_0
numpy-base 1.16.2 py36hc3f5095_0
nvidia-ml-py3 7.352.0 py_0 fastai
olefile 0.46 py_0
openpyxl 3.0.3 py_0
openssl 1.1.1d he774522_3
packaging 20.1 py_0
pandas 1.0.0 py36h47e9c7a_0
pandoc 2.2.3.2 0
pandocfilters 1.4.2 py36_1
parso 0.6.0 py_0
pickleshare 0.7.5 py36_0
pillow 7.0.0 py36hcc1f983_0
pip 20.0.2 py36_1
plac 0.9.6 py36_0
pluggy 0.13.1 py36_0
preshed 2.0.1 py36h33f27b4_0
prometheus_client 0.6.0 py36_0 esri
prompt_toolkit 3.0.3 py_0
py 1.8.1 py_0
pycparser 2.19 py_0
pygments 2.5.2 py_0
pyopenssl 19.1.0 py36_0
pyparsing 2.4.6 py_0
pypdf2 1.26.0 py_2 esri
pyrsistent 0.15.7 py36he774522_0
pyshp 1.2.12 py36_0
pysocks 1.7.1 py36_0
pytest 5.3.4 py36_0
python 3.6.8 h9f7ef89_7
python-dateutil 2.8.1 py_0
pytorch 1.1.0 py3.6_cuda100_cudnn7_1 esri
pytz 2019.3 py_0
pywavelets 1.1.1 py36he774522_0
pywin32 223 py36hfa6e2cd_1
pywin32-ctypes 0.2.0 py36_1000
pywinpty 0.5.7 py36_0
pyyaml 3.12 py36_0
pyzmq 18.1.0 py36ha925a31_0
requests 2.22.0 py36_1
scikit-image 0.15.0 py36_0 esri
scipy 1.2.1 py36h29ff71c_0
send2trash 1.5.0 py36_0
setuptools 45.1.0 py36_0
simplegeneric 0.8.1 py36_2
six 1.14.0 py36_0
soupsieve 1.9.5 py36_0
spacy 2.1.8 py36he980bc4_0 fastai
sqlite 3.30.1 he774522_0
srsly 0.1.0 py36h6538335_0 fastai
sympy 1.5.1 py36_0
terminado 0.8.3 py36_0
testpath 0.4.4 py_0
thinc 7.0.8 py36he980bc4_0 fastai
tk 8.6.8 hfa6e2cd_0
torchvision 0.2.2 py_3 pytorch
tornado 6.0.3 py36he774522_0
tqdm 4.42.0 py_0
traitlets 4.3.3 py36_0
typing 3.6.4 py36_0
urllib3 1.25.8 py36_0
vc 14.1 h0510ff6_4
vs2015_runtime 14.16.27012 hf0eaf9b_1
wasabi 0.2.2 py_0 fastai
wcwidth 0.1.7 py36_0
webencodings 0.5.1 py36_1
wheel 0.34.1 py36_0
widgetsnbextension 3.5.1 py36_0
win_inet_pton 1.1.0 py36_0
wincertstore 0.2 py36h7fe50ca_0
winkerberos 0.7.0 py36_1
winpty 0.4.3 4
x86cpu 0.4 py36_1 esri
xlrd 1.2.0 py_0
xlwt 1.3.0 py36h1a4751e_0
xz 5.2.4 h2fa13f4_4
zeromq 4.3.1 h33f27b4_3
zipp 0.6.0 py_0
zlib 1.2.11 h62dcd97_3
zstd 1.3.7 h508b16e_0(arcgis-fastai) C:\Users\username\AppData\Local\ESRI\conda\envs\arcgis-fastai>
Did you have any problems completing the required steps? What was your data path?
Automate Road Surface Investigation Using Deep Learning | ArcGIS for Developers
Hi Dan,
Tryied to replicate the issue in ArcGIS notebook Sandbox got the below error.
Any idea?
Regards,
Tauhid
Hi Dan,
I have successfully transferred the sample data using Automate Road Surface Investigation Using Deep Learning | ArcGIS for Developers into the "C:\temp\TrainingData" which is my data path. In that folder I have the subfolders images and labels.
When I try to execute the script
data = prepare_data(data_path, batch_size=4, chip_size=500, seed=42, dataset_type='PASCAL_VOC_rectangles')
It raised the error that fastai and pytorch is not installed.
Regards,
Tauhid
Have you installed the required dependencies for arcgis.learn module, you need to install the required dependencies in a clean environment and use that
conda install -c esri arcgis fastai pillow scikit-image --no-pin