Python interface for SmartRF Sniffer 2 Firmware

Overview

#TI SmartRF Packet Sniffer 2 Python Interface

TI Makes available a nice packet sniffer firmware, which interfaces to Wireshark. You can see this project here: https://www.ti.com/tool/download/PACKET-SNIFFER-2

Unfortunately sometimes you want to do stuff like scan channels, which is a hassle to do via the GUI. Luckily they document the interface.

Documentation from TI

The Documentation is installed when you install the Tool, but you can find it online.

Link to documentation: https://dev.ti.com/tirex/explore/node?node=AJ1gMrg0O1AMxi9KUZmTiQ__FUz-xrs__LATEST

Direct link to firmware interface codes: https://software-dl.ti.com/lprf/packet_sniffer_2/docs/user_guide/html/sniffer_fw/firmware/command_interface.html

Errata from TI Docs

The TI documentation claims the serial interface is at 921.6kbit baud, but on my board it was at 3Mbit baud. I'm not sure if all firmware does this or just some of the boards?

Setup

You'll need to flash the firmware onto your board. Basically ensure the GUI tool works first before trying this interface, as you'll get less feedback with this Python tool.

Scanning

For example, on my CC1352R1 board I can scan all 900 MHz channels + PHYs:

test = TICommand('COM90')

for phy in range(0, 9):
    for ch in range(0, 129):
        print("Phy = %x, Channel %d"%(phy, ch))
        test.sniff_stop()    
        test.cmd_set_frequencymhz(902.2 + 0.2*ch)
        test.cmd_set_phy(phy)
        test.sniff_start()

        rxd = 0

        for i in range(0, 3):
            time.sleep(1)

            resp = test.rx()
            if resp:
                print(resp)
                rxd += 1

Note the PHY index is specified in the reference docs from TI, as each board/chip uses different indexes. Also some of them are using the wrong frequency for the given phy etc, this is a quick-n-dirty way of doing it.

Owner
Colin O'Flynn
Colin is a huge nerd.
Colin O'Flynn
Semi Supervised Learning for Medical Image Segmentation, a collection of literature reviews and code implementations.

Semi-supervised-learning-for-medical-image-segmentation. Recently, semi-supervised image segmentation has become a hot topic in medical image computin

Healthcare Intelligence Laboratory 1.3k Jan 03, 2023
GraPE is a Rust/Python library for high-performance Graph Processing and Embedding.

GraPE GraPE (Graph Processing and Embedding) is a fast graph processing and embedding library, designed to scale with big graphs and to run on both of

AnacletoLab 194 Dec 29, 2022
DPT: Deformable Patch-based Transformer for Visual Recognition (ACM MM2021)

DPT This repo is the official implementation of DPT: Deformable Patch-based Transformer for Visual Recognition (ACM MM2021). We provide code and model

CASIA-IVA-Lab 111 Dec 21, 2022
Detection of drones using their thermal signatures from thermal camera through YOLO-V3 based CNN with modifications to encapsulate drone motion

Drone Detection using Thermal Signature This repository highlights the work for night-time drone detection using a using an Optris PI Lightweight ther

Chong Yu Quan 6 Dec 31, 2022
Code for "Sparse Steerable Convolutions: An Efficient Learning of SE(3)-Equivariant Features for Estimation and Tracking of Object Poses in 3D Space"

Sparse Steerable Convolution (SS-Conv) Code for "Sparse Steerable Convolutions: An Efficient Learning of SE(3)-Equivariant Features for Estimation and

25 Dec 21, 2022
This repository contains the files for running the Patchify GUI.

Repository Name Train-Test-Validation-Dataset-Generation App Name Patchify Description This app is designed for crop images and creating smal

Salar Ghaffarian 9 Feb 15, 2022
Fast, differentiable sorting and ranking in PyTorch

Torchsort Fast, differentiable sorting and ranking in PyTorch. Pure PyTorch implementation of Fast Differentiable Sorting and Ranking (Blondel et al.)

Teddy Koker 655 Jan 04, 2023
Convert Apple NeuralHash model for CSAM Detection to ONNX.

Apple NeuralHash is a perceptual hashing method for images based on neural networks. It can tolerate image resize and compression.

Asuhariet Ygvar 1.5k Dec 31, 2022
Implementation of our recent paper, WOOD: Wasserstein-based Out-of-Distribution Detection.

WOOD Implementation of our recent paper, WOOD: Wasserstein-based Out-of-Distribution Detection. Abstract The training and test data for deep-neural-ne

8 Dec 24, 2022
Finite difference solution of 2D Poisson equation. Can handle Dirichlet, Neumann and mixed boundary conditions.

Poisson-solver-2D Finite difference solution of 2D Poisson equation Current version can handle Dirichlet, Neumann, and mixed (combination of Dirichlet

Mohammad Asif Zaman 34 Dec 23, 2022
CZU-MHAD: A multimodal dataset for human action recognition utilizing a depth camera and 10 wearable inertial sensors

CZU-MHAD: A multimodal dataset for human action recognition utilizing a depth camera and 10 wearable inertial sensors   In order to facilitate the res

yujmo 11 Dec 12, 2022
PyTorch(Geometric) implementation of G^2GNN in "Imbalanced Graph Classification via Graph-of-Graph Neural Networks"

This repository is an official PyTorch(Geometric) implementation of G^2GNN in "Imbalanced Graph Classification via Graph-of-Graph Neural Networks". Th

Yu Wang (Jack) 13 Nov 18, 2022
Code for KiloNeRF: Speeding up Neural Radiance Fields with Thousands of Tiny MLPs

KiloNeRF: Speeding up Neural Radiance Fields with Thousands of Tiny MLPs Check out the paper on arXiv: https://arxiv.org/abs/2103.13744 This repo cont

Christian Reiser 373 Dec 20, 2022
Augmented CLIP - Training simple models to predict CLIP image embeddings from text embeddings, and vice versa.

Train aug_clip against laion400m-embeddings found here: https://laion.ai/laion-400-open-dataset/ - note that this used the base ViT-B/32 CLIP model. S

Peter Baylies 55 Sep 13, 2022
[ICLR 2022] Contact Points Discovery for Soft-Body Manipulations with Differentiable Physics

CPDeform Code and data for paper Contact Points Discovery for Soft-Body Manipulations with Differentiable Physics at ICLR 2022 (Spotlight). @InProceed

(Lester) Sizhe Li 29 Nov 29, 2022
Software Platform for solving and manipulating multiparametric programs in Python

PPOPT Python Parametric OPtimization Toolbox (PPOPT) is a software platform for solving and manipulating multiparametric programs in Python. This pack

10 Sep 13, 2022
Flybirds - BDD-driven natural language automated testing framework, present by Trip Flight

Flybird | English Version 行为驱动开发(Behavior-driven development,缩写BDD),是一种软件过程的思想或者

Ctrip, Inc. 706 Dec 30, 2022
[ICCV 2021 Oral] PoinTr: Diverse Point Cloud Completion with Geometry-Aware Transformers

PoinTr: Diverse Point Cloud Completion with Geometry-Aware Transformers Created by Xumin Yu*, Yongming Rao*, Ziyi Wang, Zuyan Liu, Jiwen Lu, Jie Zhou

Xumin Yu 317 Dec 26, 2022
Reference PyTorch implementation of "End-to-end optimized image compression with competition of prior distributions"

PyTorch reference implementation of "End-to-end optimized image compression with competition of prior distributions" by Benoit Brummer and Christophe

Benoit Brummer 6 Jun 16, 2022
This is the official implementation for the paper "(Almost) Free Incentivized Exploration from Decentralized Learning Agents" in NeurIPS 2021.

Observe then Incentivize Experiments This is the code used for the paper "(Almost) Free Incentivized Exploration from Decentralized Learning Agents",

Cong Shen Research Group 0 Mar 08, 2022