tensorflow-on-raspberry-pi | TensorFlow for Raspberry Pi

by samjabrahams Python Version: v1.1.0 License: Non-SPDX

X-Ray Key Features Code Snippets(3)Community Discussions(3)Vulnerabilities Install Support

kandi X-RAY | tensorflow-on-raspberry-pi Summary

tensorflow-on-raspberry-pi is a Python library typically used in Internet of Things (IoT), Tensorflow, Raspberry Pi applications. tensorflow-on-raspberry-pi has no bugs, it has no vulnerabilities and it has medium support. However tensorflow-on-raspberry-pi build file is not available and it has a Non-SPDX License. You can download it from GitHub.

TensorFlow for Raspberry Pi

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Security

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Support

tensorflow-on-raspberry-pi has a medium active ecosystem.

It has 2208 star(s) with 507 fork(s). There are 179 watchers for this library.

It had no major release in the last 12 months.

There are 73 open issues and 80 have been closed. On average issues are closed in 113 days. There are 1 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of tensorflow-on-raspberry-pi is v1.1.0

Quality

tensorflow-on-raspberry-pi has 0 bugs and 0 code smells.

Security

tensorflow-on-raspberry-pi has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

tensorflow-on-raspberry-pi code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

tensorflow-on-raspberry-pi has a Non-SPDX License.

Non-SPDX licenses can be open source with a non SPDX compliant license, or non open source licenses, and you need to review them closely before use.

Reuse

tensorflow-on-raspberry-pi releases are available to install and integrate.

tensorflow-on-raspberry-pi has no build file. You will be need to create the build yourself to build the component from source.

Installation instructions, examples and code snippets are available.

tensorflow-on-raspberry-pi saves you 2040 person hours of effort in developing the same functionality from scratch.

It has 4482 lines of code, 8 functions and 727 files.

It has high code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi has reviewed tensorflow-on-raspberry-pi and discovered the below as its top functions. This is intended to give you an instant insight into tensorflow-on-raspberry-pi implemented functionality, and help decide if they suit your requirements.

Runs inference on an image
Create a graph from saved graph_def
Download and extract the model

Get all kandi verified functions for this library.

tensorflow-on-raspberry-pi Key Features

No Key Features are available at this moment for tensorflow-on-raspberry-pi.

tensorflow-on-raspberry-pi Examples and Code Snippets

为树莓派安装tensorflow

HTML

Lines of Code : 19

License : No License

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# For Python 2.7
sudo apt-get install python-pip python-dev

# For Python 3.3+
sudo apt-get install python3-pip python3-dev

# For Python 2.7
wget https://github.com/samjabrahams/tensorflow-on-raspberry-pi/releases/download/v1.0.1/tensorflow-1.0.1-cp

Computer vision libs and techniques for Ramudroid,Raspberry Pi camera module,Deep Learning

Python

Lines of Code : 2

License : No License

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pip3 install tensorflow
pip3 install keras

For Raspbian

Python

Lines of Code : 1

License : Permissive (Apache-2.0)

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sudo pip3 install numpy opencv-python scipy scikit-learn h5py

Community Discussions

Trending Discussions on tensorflow-on-raspberry-pi

Tensorflow 1.5 on Raspberry Pi3

Building bazel from source - Getting Failed

conda install - six, wheel, numpy, protobuf, werkzeug

QUESTION

Tensorflow 1.5 on Raspberry Pi3

Asked 2018-Apr-30 at 00:37

I followed these instructions to compile tensorflow: https://github.com/samjabrahams/tensorflow-on-raspberry-pi/blob/master/GUIDE.md

I pulled the newest bazel (0.9.0)from github and compiled it successfully. After that I pulled the newest tensorflow (1.5.0) from github then applied this command

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ANSWER

Answered 2018-Apr-30 at 00:37

It is looking for ConcatCPU defined here: https://github.com/tensorflow/tensorflow/blob/r1.5/tensorflow/core/kernels/concat_lib_cpu.cc#L51

Source https://stackoverflow.com/questions/48553812

QUESTION

Building bazel from source - Getting Failed

Asked 2018-Apr-12 at 18:24

The objective of my experiment is to build tensorflow on Jetson TK1 arm based embedded board. Since pre-builts of tensorflow for arm architecture are not given by the official releases, I was forced to the option of building it from source.

To build tensorflow, we need Bazel which should be also build from source. Now I got stuck here, not able to build bazel at all.

I have referred various blogs and github projects and tried to follow the instructions everyone said it worked for them.

1) Tensorflow on Raspberry-pi

2) Jetson Hacks building Tensorflow from source

3) Official Documentation

Steps Followed:

...

ANSWER

Answered 2018-Apr-12 at 14:32

Version 0.4.5 is very old. We just released 0.12.0, could you try that one?

Source https://stackoverflow.com/questions/49794727

QUESTION

conda install - six, wheel, numpy, protobuf, werkzeug

Asked 2017-Nov-07 at 01:37

I installed conda version of opencv - opencv 3.2 + python 3.4.3 . after that i tried to install tensorflow using

...

ANSWER

Answered 2017-Sep-13 at 12:08

Here is the command line you ask for:

conda install package=version

package is the name of the module you want to install
version is the version number (like 1.2.3)

Source https://stackoverflow.com/questions/46197106

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install tensorflow-on-raspberry-pi

You can install the official wheel with the following commands, assuming you are using Raspbian 9:. It was a fun ride! With Raspberry Pi support now official, I will no longer be looking to update this repository. I'm sorry that I wasn't able to continue maintaining the repo as much as I wanted, but it was amazing watching the community continue to thrive.

Support

As of TensorFlow 1.9, Python wheels for TensorFlow are being officially supported. As such, this repository is no longer recommended for your TensorFlow on RPi needs; use the official sources!.

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