image3c 0.1.4

Creator: bradpython12

Last updated:

Add to Cart

Description:

image3c 0.1.4

Instructions for training and prediction
Installation of python

For best performance an NVIDIA GPU with CUDA is recommended

Install requirements for TensorFlow

tensorflow_gpu-1.15.0 3.3-3.7

NVIDIA drivers

Linux : >= 410.48
Windows : >= 411.31


cuDNN 7.6 (See below to install with conda)
CUDA 10.2 (See below to install with conda)



The steps
below
install the CUDA libraries during the conda environment setup,
but if you want more information about it see these links:


For more detail about using conda to install CUDA see this article:
Install CUDA with conda


For more information regarding installation of CUDA, see this document:
NVIDIA CUDA


Install miniconda (recommended) or anaconda
We recommend using conda
as an environment and package manager. It will allow easily creating python
environments with specific version and package needs. If you already have Anaconda
installed it will work and the instructions below will be the same.

Download miniconda for your platform.
Follow the installation documentation for the target operating system:

Windows
Linux
Mac



After installation, open a terminal to start installing packages. On Windows find the
Anaconda Prompt command using the search tool.
Create a conda environment
Image3c requires version 3.7 of python and TensorFlow version 1.15, so a fresh conda
enviroment is recommended. We have written an environment file the takes care of
creating the conda environment and installing all needed dependencies. If you are on
MacOS or don't have an NVIDA GPU with CUDA use environment.yml. If you are on Windows
or Linux and have a CUDA GPU then use environment_gpu.yml
Creating the conda environment in this way also installs the correct CUDA
libraries in the conda python environment.
In the following command, a conda environment
named image3c is created with python 3.7:
conda env create -f environment.yml
if on windows or linux with a CUDA gpu
conda env create -f environment_gpu.yml
To activate this environment, use this command:
conda activate image3c
The image3c python package is installed during the creation of the conda
environment, so no other installation command are needed.
Install image3c from pip
If you don't want to create an environment as described above, image3c can
be installed with pip:
pip install image3c
How to use Image3c
The main documentation can be found at:
Image3c Github
Jupyter notebooks giving details about training and predicting
data from the ImageStream can be found in the main pages of this github repository:
Classifier Notebooks.

License

For personal and professional use. You cannot resell or redistribute these repositories in their original state.

Customer Reviews

There are no reviews.