In RQ based environment, anew worker will be forked every time work is assigned. RQ based worker works in an independent context every time.
While designing system workflow using task queues, we might end up situations like, one job waiting for multiple other jobs to complete. In celery we have chords and groups to handle this. How can we do this in python-rq ?
how will we do visualization of results? Copy the data to local computer and view it separetely? We can do that.. but, is there a better way? Yes. We can enable docker with GUI capabilities and display contents from docker itself.
In this post, I will try to cover how to use tensorflow docker image for various use cases. In this post, we will see what bare-minimum required to be installed on the computer.
FFmpeg is a great software package a media developer should have. The kind of configurability this provides is uncomparable in media domain. Out of vast capabilities, this article discusses how one can extract frames from video.
I got a new laptop. What next? Check what is there inside. 9 th Generation Intel® Core™ i5 processor NVIDIA® GeForce® GTX 1650 Graphics(4 GB GDDR5 dedicated) Now, I want to test the GPU
We have different solutions available for streaming mpeg2ts content over rtp.