Μηνιαία αρχεία: Μάρτιος 2022

A very good reason to avoid Google Pixel 6 and get a Google Pixel 5 instead

 στο Google  επισημασμένο με ετικέτα free / google / phone / photos / pixel / storage Από

After reading this help center page (Choose the upload size of your photos & videos):

We realized that while Google provides free storage for Google photos (one way or the other) to older versions of Google Pixel phones (including version 5), they do not offer any free storage for their newest series, Google Pixel 6.

Having a phone with a fantastic camera but being unable to use the backup mechanism freely without paying sucks. The more one user operates the camera, the more space they will require, making their account storage fill up.

For this reason, as Google Pixel Series 5 has a decent camera, we strongly consider purchasing an older phone and saving money in the long run through the free backup mechanism for photos.

Compiling ffmpeg with NVIDIA GPU Hardware Acceleration on Ubuntu 20.04LTS

 στο Applications  επισημασμένο με ετικέτα cuda / ffmpeg / GPU / nvidia / ubuntu Από

Please note that the following commands were executed on a system that already had CUDA support so we might be missing a step or two to enable NVIDIA CUDA support.

Install necessary packages

sudo apt-get install build-essential yasm cmake libtool libc6 libc6-dev unzip wget libnuma1 libnuma-dev nvidia-cuda-toolkit;

Clone and install ffnvcodec

git clone https://git.videolan.org/git/ffmpeg/nv-codec-headers.git;
cd nv-codec-headers;
sudo make install;
cd -;

Clone and compile FFmpeg’s public GIT repository with NVIDIA GPU hardware acceleration

git clone https://git.ffmpeg.org/ffmpeg.git ffmpeg/;
cd ffmpeg;
./configure --enable-nonfree --enable-cuda-nvcc --enable-libnpp --extra-cflags=-I/usr/local/cuda/include --extra-ldflags=-L/usr/local/cuda/lib64 --disable-static --enable-shared;
make -j 8;
sudo make install;

SUCCESS!

After performing the above steps, we were able to process media using ffmpeg without stressing our CPU! The workload was transferred to the GPU!