simple-tensor 0.4.21

a simple package for handling tensorflow tensor

README

NEWS

Date	News	Version
March 2019	simple_tensor is available on pypi (pip3 install simple-tensor)	>=v0.4.0
March 2019	Add Inceptionv4 and Densenet for transfer-learning package	v0.4.3
29th March 2019	Simple tensor for Tensorflow 1.13.1 is available on pypi	v0.4.3
	n
April 2019	yolov3 (preview version)	v0.4.18
April 2019	Unet-segmentation (preview version)	v0.4.18

Tensorflow Compatibility

Tensorflow version	Simple-Tensor Version
1.4.1 - 1.12	>=v0.4.0
1.3.1	>=v0.4.3

ABOUT PROJECT

This is a simplification of tensorflow operations and related projects

DEPENDENCIES

1. Tensorflow (1.4.1 - 1.13)

For installing tensorflow, with GPU:

# python3 
pip3 install tensorflow-gpu
# python2
pip2 install tensorflow-gpu

Without GPU:

# python3 
pip3 install tensorflow
# python2
pip2 install tensorflow

HOW TO USE

:shipit: Installing The Package

python setup.py install

or

pip3 install simple-tensor

:shipit: Import The Package

• Tensor Operations

import tensorflow as tf
from simple_tensor.tensor_operations import *

  For more detail documentations about tensor operations, visit this page

• Convert Keras Model to Tensorflow Serving

import tensorflow as tf
from simple_tensor.convert import *

• Transfer Learning Package

import tensorflow as tf
from simple_tensor.transfer_learning.inception_utils import *
from simple_tensor.transfer_learning.inception_v4 import *

  For more detail documentations about transfer learning package, visit this page

• Object Detector Package

import tensorflow as tf
from simple_tensor.object_detector.detector_utils import *
from simple_tensor.object_detector.yolo_v4 import *

  For more detail documentations about object detector package (yolov3), visit this page. This package still in preview mode or unstable.

• Unet Segmentation Package

still on progress ....

• LSTM Package

still on progress ....

DOCKER

We already prepared the all in one docker for computer vision and deep learning libraries, including tensorflow 1.12, Opencv3.4.2 and contrib, CUDA 9, CUDNN 7, Keras, jupyter, numpy, sklearn, scipy, statsmodel, pandas, matplotlib, seaborn, flask, gunicorn etc. See the list of dockerfile below:

Docker: Ubuntu 16.04 with GPU (Cuda 9, cudnn 7.2) [TESTED]

• https://github.com/fatchur/Opencv-contribt-Tensorflow-GPU-DS-Tools-Docker/tree/master/docker-16.04

Docker: Ubuntu 18.04 with GPU (Cuda 9, cudnn 7.2)

• https://github.com/fatchur/Opencv-contribt-Tensorflow-GPU-DS-Tools-Docker/tree/master/docker-18.04

Docker: Ubuntu 16.04 without GPU (Cuda 9, cudnn 7.2) [TESTED]

• https://github.com/fatchur/Opencv-contribt-Tensorflow-GPU-DS-Tools-Docker/tree/without_gpu/docker-16.04

Docker: Ubuntu 18.04 without GPU (Cuda 9, cudnn 7.2) [TESTED]

• https://github.com/fatchur/Opencv-contribt-Tensorflow-GPU-DS-Tools-Docker/tree/without_gpu/docker-18.04