Camera-caps - Examine the camera capabilities for V4l2 cameras

Overview

camera-caps

This is a graphical user interface over the v4l2-ctl command line tool. This program supports an upcoming JetsonHacks article and video.

Intended Spirit

This app is a simple software sketch built to support a demonstration. It is not fully featured, and certainly not production quality code, but you may find it useful for your own study and experimentation.

On the NVIDIA Jetson family of products, connected cameras generally stream through the V4L2 module. USB cameras go through the uvcvideo module which interfaces with the v4l2 module. Cameras connected through the CSI/MIPI ports (Raspberry Pi camera, GMSL cameras for example) interface with the tegra-video module, which in turn interfaces with the v4l2 module.

Connected cameras show up as /dev/videoX (where X is the ID number) when connected with the proper drivers installed. Properly connected and registered, you can use the v4l2-ctl utility to examine the properties of the cameras. This includes the available pixel formats, frame sizes, frame rates, and properties. There are controls to adjust the properties of the camera. The GUI provides a consolidated view:

Screenshot

Note

Not all cameras provide a V4L2 interface. Some cameras have proprietary interfaces that are not exposed through V4L2.

Installation

$ sudo apt update
$ sudo apt install python3-pip
$ pip3 install dataclasses
# Install v4l2-ctl
$ sudo apt install v4l-utils

Running the Program

Before running the program, first make sure that the cameras you want to examine are attached. The program does not detect dynamic attachment. If you plug/unplug a camera, restart the program. Also note that USB cameras do not have a guaranteed address in their /dev/videoX designation. In other words, the address may change when the machine reboots or other cameras are added. To run:

$ python3 camera_caps.py

The preview button attempts to build a GStreamer pipeline and run it in a preview window. The preview window is not the full size of the video image size.

Releases

January, 2022

  • Initial Release
  • JetPack 4.6, L4T 32.6.1
  • Test on Jetson Nano, Jetson Xavier NX - Other Jetsons should work
Owner
Jetsonhacks
Code for NVIDIA Jetson Developer Kits. Please note that Jetson Nano code is on https://github.com/jetsonhacksnano
Jetsonhacks
Unoffical implementation about Image Super-Resolution via Iterative Refinement by Pytorch

Image Super-Resolution via Iterative Refinement Paper | Project Brief This is a unoffical implementation about Image Super-Resolution via Iterative Re

LiangWei Jiang 2.5k Jan 02, 2023
Gated-Shape CNN for Semantic Segmentation (ICCV 2019)

GSCNN This is the official code for: Gated-SCNN: Gated Shape CNNs for Semantic Segmentation Towaki Takikawa, David Acuna, Varun Jampani, Sanja Fidler

859 Dec 26, 2022
Classifies galaxy morphology with Bayesian CNN

Zoobot Zoobot classifies galaxy morphology with deep learning. This code will let you: Reproduce and improve the Galaxy Zoo DECaLS automated classific

Mike Walmsley 39 Dec 20, 2022
CTF challenges from redpwnCTF 2021

redpwnCTF 2021 Challenges This repository contains challenges from redpwnCTF 2021 in the rCDS format; challenge information is in the challenge.yaml f

redpwn 27 Dec 07, 2022
ParaGen is a PyTorch deep learning framework for parallel sequence generation

ParaGen is a PyTorch deep learning framework for parallel sequence generation. Apart from sequence generation, ParaGen also enhances various NLP tasks, including sequence-level classification, extrac

Bytedance Inc. 169 Dec 22, 2022
MINOS: Multimodal Indoor Simulator

MINOS Simulator MINOS is a simulator designed to support the development of multisensory models for goal-directed navigation in complex indoor environ

194 Dec 27, 2022
Privacy as Code for DSAR Orchestration: Privacy Request automation to fulfill GDPR, CCPA, and LGPD data subject requests.

Meet Fidesops: Privacy as Code for DSAR Orchestration A part of the greater Fides ecosystem. ⚡ Overview Fidesops (fee-dez-äps, combination of the Lati

Ethyca 44 Dec 06, 2022
"Inductive Entity Representations from Text via Link Prediction" @ The Web Conference 2021

Inductive entity representations from text via link prediction This repository contains the code used for the experiments in the paper "Inductive enti

Daniel Daza 45 Jan 09, 2023
Contains code for the paper "Vision Transformers are Robust Learners".

Vision Transformers are Robust Learners This repository contains the code for the paper Vision Transformers are Robust Learners by Sayak Paul* and Pin

Sayak Paul 103 Jan 05, 2023
Construct a neural network frame by Numpy

本项目的CSDN博客链接:https://blog.csdn.net/weixin_41578567/article/details/111482022 1. 概览 本项目主要用于神经网络的学习,通过基于numpy的实现,了解神经网络底层前向传播、反向传播以及各类优化器的原理。 该项目目前已实现的功

24 Jan 22, 2022
Open source repository for the code accompanying the paper 'PatchNets: Patch-Based Generalizable Deep Implicit 3D Shape Representations'.

PatchNets This is the official repository for the project "PatchNets: Patch-Based Generalizable Deep Implicit 3D Shape Representations". For details,

16 May 22, 2022
Online Multi-Granularity Distillation for GAN Compression (ICCV2021)

Online Multi-Granularity Distillation for GAN Compression (ICCV2021) This repository contains the pytorch codes and trained models described in the IC

Bytedance Inc. 299 Dec 16, 2022
Official Implementation for "StyleCLIP: Text-Driven Manipulation of StyleGAN Imagery" (ICCV 2021 Oral)

StyleCLIP: Text-Driven Manipulation of StyleGAN Imagery (ICCV 2021 Oral) Run this model on Replicate Optimization: Global directions: Mapper: Check ou

3.3k Jan 05, 2023
Code for "Learning Graph Cellular Automata"

Learning Graph Cellular Automata This code implements the experiments from the NeurIPS 2021 paper: "Learning Graph Cellular Automata" Daniele Grattaro

Daniele Grattarola 37 Oct 26, 2022
Code from Daniel Lemire, A Better Alternative to Piecewise Linear Time Series Segmentation

PiecewiseLinearTimeSeriesApproximation code from Daniel Lemire, A Better Alternative to Piecewise Linear Time Series Segmentation, SIAM Data Mining 20

Daniel Lemire 21 Oct 27, 2022
Unofficial implementation of "Coordinate Attention for Efficient Mobile Network Design"

Unofficial implementation of "Coordinate Attention for Efficient Mobile Network Design". CoordAttention tensorflow slim

Billy 9 Aug 22, 2022
Official implementation of the NeurIPS'21 paper 'Conditional Generation Using Polynomial Expansions'.

Conditional Generation Using Polynomial Expansions Official implementation of the conditional image generation experiments as described on the NeurIPS

Grigoris 4 Aug 07, 2022
Recursive Bayesian Networks

Recursive Bayesian Networks This repository contains the code to reproduce the results from the NeurIPS 2021 paper Lieck R, Rohrmeier M (2021) Recursi

Robert Lieck 11 Oct 18, 2022
Mercer Gaussian Process (MGP) and Fourier Gaussian Process (FGP) Regression

Mercer Gaussian Process (MGP) and Fourier Gaussian Process (FGP) Regression We provide the code used in our paper "How Good are Low-Rank Approximation

Aristeidis (Ares) Panos 0 Dec 13, 2021
EgoNN: Egocentric Neural Network for Point Cloud Based 6DoF Relocalization at the City Scale

EgonNN: Egocentric Neural Network for Point Cloud Based 6DoF Relocalization at the City Scale Paper: EgoNN: Egocentric Neural Network for Point Cloud

19 Sep 20, 2022