Μηνιαία αρχεία: Νοέμβριος 2021

Playing with MASK RCNN on videos .. again

 στο Artificial intelligence / Deep Learning / Machine Learning / Neural Networks  επισημασμένο με ετικέτα ai / anaconda / artificial intelligence / bash / CNN / conda / convolutional neural network / Feature Pyramid Network / GNU/Linux / keras / mask / MASK RCNN / object detection / opencv / python / RCNN / ResNet101 / TensorFlow / ubuntu Από

Source code for the implementation that created this video will be uploaded soon.

A first attempt at using a pre-trained implementation of Mask R-CNN on Python 3, Keras, and TensorFlow. The model generates bounding boxes and segmentation masks for each instance of an object in each frame. It’s based on Feature Pyramid Network (FPN) and a ResNet101 backbone.

Setup

Conda / Anaconda

First of all, we installed and activated anaconda on an Ubuntu 20.04LTS desktop. To do so, we installed the following dependencies from the repositories:

sudo apt-get install libgl1-mesa-glx libegl1-mesa libxrandr2 libxrandr2 libxss1 libxcursor1 libxcomposite1 libasound2 libxi6 libxtst6;

Then, we downloaded the 64-Bit (x86) Installer from (https://www.anaconda.com/products/individual#linux).

Using a terminal, we followed the instructions here (https://docs.anaconda.com/anaconda/install/linux/) and performed the installation.

Python environment and OpenCV for Python

Following the previous step, we used the commands below to create a virtual environment for our code. We needed python version 3.9 (as highlighted here https://www.anaconda.com/products/individual#linux) and OpenCV for python.

source ~/anaconda3/bin/activate;
conda create --name MaskRNN python=3.9;
conda activate MaskRNN;
pip install numpy opencv-python;

Problems that we did not anticipate

When we tried to execute our code in the virtual environment:

python3 main.py --video="/home/bob/Videos/Live @ Santa Claus Village 2021-11-13 12_12.mp4";

We got the following error:

Traceback (most recent call last):
  File "/home/bob/MaskRCNN/main.py", line 6, in <module>
    from cv2 import cv2
  File "/home/bob/anaconda3/envs/MaskRNN/lib/python3.9/site-packages/cv2/__init__.py", line 180, in <module>
    bootstrap()
  File "/home/bob/anaconda3/envs/MaskRNN/lib/python3.9/site-packages/cv2/__init__.py", line 152, in bootstrap
    native_module = importlib.import_module("cv2")
  File "/home/bob/anaconda3/envs/MaskRNN/lib/python3.9/importlib/__init__.py", line 127, in import_module
    return _bootstrap._gcd_import(name[level:], package, level)
ImportError: libGL.so.1: cannot open shared object file: No such file or directory

We realized that we were missing some additional dependencies for OpenCV as our Ubuntu installation was minimal. To fix this issue, we installed the following package from the repositories:

sudo apt-get update;
sudo apt-get install -y python3-opencv;

How to Start/Stop or Enable/Disable firewalld on CentOS 8

 στο GNU/Linux  επισημασμένο με ετικέτα CentOS / centos 8 / firewall / firewalld / GNU/Linux Από

firewalld (Dynamic Firewall Manager) tool provides a dynamically managed firewall. The tool enables network/firewall zones to define the trust level of network connections and/or interfaces. It has support both for IPv4 and IPv6 firewall settings. Also, it supports Ethernet bridges and allow you to separate between runtime and permanent configuration options. Finally, it supports an interface for services or applications to add firewall rules directly.

Disable firewalld

To disable firewalld, execute the following command as root or using sudo:

systemctl disable firewalld

Enable firewalld

To enable firewalld, execute the following command as root or using sudo:

systemctl enable firewalld

Stop firewalld

To stop (or deactivate) firewalld,execute the following command as root or using sudo:

systemctl stop firewalld

Start firewalld

To start (or activate) firewalld, execute the following command as root or using sudo:

systemctl start firewalld

Status of firewalld

To check the status of firewalld, execute the following command as root or using sudo:

systemctl status firewalld

CONCEPTS

systemd provides a dependency system between various entities called “units” of 12 different types. Units encapsulate various objects that are relevant for system boot-up and maintenance. The majority of units are configured in unit configuration files, whose syntax and basic set of options is described in systemd.unit(5), however some are created automatically from other configuration, dynamically from system state or programmatically at runtime. Units may be “active” (meaning started, bound, plugged in, …, depending on the unit type, see below), or “inactive” (meaning stopped, unbound, unplugged, …), as well as in the process of being activated or deactivated, i.e. between the two states (these states are called “activating”, “deactivating”). A special “failed” state is available as well, which is very similar to “inactive” and is entered when the service failed in some way (process returned error code on exit, or crashed, or an operation timed out). If this state is entered, the cause will be logged, for later reference. Note that the various unit types may have a number of additional substates, which are mapped to the five generalized unit states described here.
— From man systemd

The above, in a nutshell:

  • enabled is a service that is configured to start when the system boots
  • disabled is a service that is configured to not start when the system boots
  • active is a service that is currently running
  • inactive is a service that is currently stopped and may be disabled, but it can be started and become active

Some notes on how to record audio from a terminal in Ubuntu 20.04LTS

 στο Bash / GNU/Linux  επισημασμένο με ετικέτα audio / bash / ffmpeg / GNU/Linux / linux / pactl / record / terminal / ubuntu / ubuntu 20.04LTS Από

Recently, we were trying to record the audio that was played on the system speakers using an Ubuntu 20.04LTS desktop. In the installation, there was no dedicated audio recorder installed and we did not want to install any. To record, we used the following command to get the list of all audio sources available to the system:

pactl list short sources;

The pactl command produced results like so:

3	alsa_output.pci-0000_00_1f.3.analog-stereo.monitor	module-alsa-card.c	s16le 2ch 44100Hz	SUSPENDED
4	alsa_input.pci-0000_00_1f.3.analog-stereo	module-alsa-card.c	s16le 2ch 44100Hz	SUSPENDED
10	alsa_input.usb-Dell_DELL_PROFESSIONAL_SOUND_BAR_AE515-00.iec958-stereo	module-alsa-card.c	s16le 2ch 44100Hz	SUSPENDED
12	alsa_output.usb-Dell_DELL_PROFESSIONAL_SOUND_BAR_AE515-00.analog-stereo.monitor	module-alsa-card.c	s16le 2ch 44100Hz	IDLE

We knew that the system was using the Dell soundbar in analog mode to play the music (as we could see in the Settings under the Sound category, which is depicted below), so we copied the following name from the line that starts with the number 12:

alsa_output.usb-Dell_DELL_PROFESSIONAL_SOUND_BAR_AE515-00.analog-stereo.monitor

Then we used that monitor name as an input device for FFmpeg like so:

ffmpeg -f pulse -i alsa_output.usb-Dell_DELL_PROFESSIONAL_SOUND_BAR_AE515-00.analog-stereo.monitor test.mp3;

When we were done recording, we pressed CTRL+C to stop the recording.