|
|
|
A **manual installation** is always possible.
|
|
|
|
|
|
|
|
This solution can be adapted if the procedure described above does not work.\
|
|
|
|
This can be the case, for example under MacOS.
|
|
|
|
|
|
|
|
## First install Tensorflow from the official install procedure
|
|
|
|
|
|
|
|
The easiest way is to follow the official procedure proposed on the Tensorflow website:
|
|
|
|
|
|
|
|
**https://www.tensorflow.org/install/pip?hl=fr**
|
|
|
|
|
|
|
|
## Required additional packages for Fidle
|
|
|
|
|
|
|
|
Once Tensorflow is installed following the official procedure, you must install the following additional modules:
|
|
|
|
|
|
|
|
* Scikit-image
|
|
|
|
* Scikit-learn
|
|
|
|
* Matplotlib
|
|
|
|
* Pandas
|
|
|
|
* Pandoc
|
|
|
|
* pyyaml
|
|
|
|
* Jupyter lab
|
|
|
|
|
|
|
|
If you have followed the official pip procedure, you should be able to install these modules with the command :
|
|
|
|
|
|
|
|
```
|
|
|
|
pip install Scikit-image Scikit-learn Matplotlib Pandas Pandoc Jupyterlab
|
|
|
|
```
|
|
|
|
|
|
|
|
## Start Jupyter lab
|
|
|
|
|
|
|
|
1. Set your environment var
|
|
|
|
- Linux : `export FIDLE_DATASETS_DIR=<path to the datasets dir>`
|
|
|
|
- Windows : `set FIDLE_DATASETS_DIR=<path to the datasets dir>`
|
|
|
|
2. From your Python environment :
|
|
|
|
`jupyter lab`
|
|
|
|
|
