All Projects → jetsonhacks → installTensorFlowJetsonTX

jetsonhacks / installTensorFlowJetsonTX

Licence: MIT license
Install TensorFlow on the NVIDIA Jetson TX1 or TX2 from the provided wheel files

Projects that are alternatives of or similar to installTensorFlowJetsonTX

jetsonUtilities
Get information about the NVIDIA Jetson OS environment. Lists L4T and JetPack versions, along with major libraries.
Stars: ✭ 171 (+116.46%)
Mutual labels:  jetson-tx1, jetson-tx2
gpuGraphTX
Simple moving graph of GPU activity for the Jetson TX1 and Jetson TX2
Stars: ✭ 92 (+16.46%)
Mutual labels:  jetson-tx1, jetson-tx2
Jetson Inference
Hello AI World guide to deploying deep-learning inference networks and deep vision primitives with TensorRT and NVIDIA Jetson.
Stars: ✭ 5,191 (+6470.89%)
Mutual labels:  jetson-tx1, jetson-tx2
installROS
Install ROS Melodic on NVIDIA Jetson Development Kits
Stars: ✭ 75 (-5.06%)
Mutual labels:  jetson-tx1, jetson-tx2
DLARM
DLARM: Dissertation for Computer Science Masters Degree at UFRGS
Stars: ✭ 24 (-69.62%)
Mutual labels:  jetson-tx1, jetson-tx2
installRACECARJ
Install the ROS stack, MIT RACECAR Packages, and hardware support on RACECAR/J.
Stars: ✭ 28 (-64.56%)
Mutual labels:  jetson-tx1, jetson-tx2
jetson csi cam
A ROS package making it simple to use CSI cameras on the Nvidia Jetson TK1, TX1, or TX2 with ROS.
Stars: ✭ 95 (+20.25%)
Mutual labels:  jetson-tx1, jetson-tx2
jetson-tx2-pytorch
Installing PyTorch on the Nvidia Jetson TX1/TX2
Stars: ✭ 74 (-6.33%)
Mutual labels:  jetson-tx1, jetson-tx2
installACMModule
Install the CDC ACM and USB to Serial Modules for the Jetson TX1 or Jetson TX2 Development Kit
Stars: ✭ 28 (-64.56%)
Mutual labels:  jetson-tx1, jetson-tx2
nvidia-jetson-rt
Real-Time Scheduling with NVIDIA Jetson TX2
Stars: ✭ 38 (-51.9%)
Mutual labels:  jetson-tx2
Autonomous-RC-Car
Self-driving RC Car ROS Software
Stars: ✭ 17 (-78.48%)
Mutual labels:  jetson-tx2
dd performances
DeepDetect performance sheet
Stars: ✭ 92 (+16.46%)
Mutual labels:  jetson-tx1
keras-tensorrt-jetson
Example of loading a Keras model into TensorRT C++ API
Stars: ✭ 51 (-35.44%)
Mutual labels:  jetson-tx2
Torch2trt
An easy to use PyTorch to TensorRT converter
Stars: ✭ 2,974 (+3664.56%)
Mutual labels:  jetson-tx2
homesecurity
Security camera with Raspberry pi and NVIDIA Jetson platforms
Stars: ✭ 141 (+78.48%)
Mutual labels:  jetson-tx2
ros jetson stats
🐢 The ROS jetson-stats wrapper. The status of your NVIDIA jetson in diagnostic messages
Stars: ✭ 55 (-30.38%)
Mutual labels:  jetson-tx2
cibuildwheel
🎡 Build Python wheels for all the platforms on CI with minimal configuration.
Stars: ✭ 1,350 (+1608.86%)
Mutual labels:  python-wheels
arm-wheels
Project to generate Python wheels for ARM systems (targeting armv7 / aarch64 in the future)
Stars: ✭ 14 (-82.28%)
Mutual labels:  python-wheels
wheelfile
🔪🧀 API for creating and inspecting Python .whl files (wheels).
Stars: ✭ 22 (-72.15%)
Mutual labels:  python-wheels
YOLOP
You Only Look Once for Panopitic Driving Perception.(https://arxiv.org/abs/2108.11250)
Stars: ✭ 1,228 (+1454.43%)
Mutual labels:  jetson-tx2

installTensorFlowJetsonTX

Install TensorFlow on the NVIDIA Jetson TX1 or TX2 from the provided wheel files

Python .whl files for installing TensorFlow.

Installation

There are two directories in this repository, TX1 and TX2. First, install the matching pip for your Python installation. Then install the wheel file from the directory that matches your Jetson model, and version of Python:

Python 2.7

$ sudo apt-get install -y python-pip python-dev

$ pip install tensorflow-wheel-file

Python 3.5

$ sudo apt-get install -y python3-pip python3-dev

$ pip3 install tensorflow-wheel-file

Build Information

There are wheel files for Python 2.7 and Python 3.5 The Jetson environment:

  • L4T 28.1 (JetPack 3.1)
  • CUDA 8.0
  • cuDNN 6.0

TensorFlow

  • Version 1.3.0
  • Built with CUDA support

Full directions used for building the wheel files:

Note: The Jetson TX1 uses a GPU architecture to 5.3, the Jetson TX2 is 6.2. The builds reflect this.

Note that the project description data, including the texts, logos, images, and/or trademarks, for each open source project belongs to its rightful owner. If you wish to add or remove any projects, please contact us at [email protected].