Dependencies are managed through pipenv.
For Raspberry Pi:
We are using python
= 3.4.4
with:
`tensorflow` = `1.1.0`
`numpy` = `1.11.0`
This is due to the available pre-compiled Tensorflow wheel for Pi being 1.1.0
which only supports python 3.4.4
.
Unfortunately numpy-extensions > 1.11.0
does not work properly on python 3.4.4
so we are locked to numpy 1.11.0
for the time being as well.
- Download the Tensorflow 1.1.0 wheel from here and place it in the project root directory.
- Edit the Pipfile:
- Comment out
tensorflow = "==1.1.0"
- Comment out
opencv-python = "*"
- Uncomment
"c0a73bc" = {path = "./tensorflow...whl"}
- Comment out
- run
pipenv install --skip-lock
- Edit the Pipfile:
- Comment out
"c0a73bc" = {path = "./tensorflow...whl"}
- Uncommment any other line
- Comment out
- run
pipenv install --skip-lock
- Check if your Python version is running on 64-bit arch, re-install if it isn't
- Run the following in a Python shell to check
>>> import platform
>>> platform.architecture()
- Run the following in a Python shell to check
- Edit the Pipfile:
- Comment out
numpy = "==1.11.*"
- Comment out
tensorflow = "==1.1.0"
- Comment out
"c0a73bc" = {path = "./tensorflow...whl"}
- Run
pipenv shell
- Run
pipenv install --skip-lock
- Run
pipenv install --upgrade tensorflow
- Comment out
- Make sure the current shell is a virtualenv shell by running
pipenv shell
in the project root directory. - Run
python app.py -db
to set up database - Run
python app.py
to start server