I have encountered an issue during develop HLS live streaming through Django restframework.
Currently, I have a shell script that generates HLS files(m3u8), and now I am confused about how to respond the generated HLS files to the frontend so that the user able to view the HLS streaming from web.
I did a little bit research on this, looks some developers suggest use Django serve, but I am confused will it be enough if I only return the m3u8 to the frontend.
HLS source files generated from ffmpeg
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I am working on a system that will work on the local network , for some reason users will not have access to the internet, the only access that allowed to those users is my server, and my server has full access to the internet, so what I want is to stream video from youtube to my server to my client
youtube -----> server ------>client
I searched a lot but I could found any things that might help me, most of the people talked about streaming live videos which I don't want, I want to stream any video on youtube to my server, then the client will get the video from my server.
is it possible to do this?
I am using laravel to develop my system, but I can use python / node js if it is not possible in laravel
I think you can take a look at pytube package.
you can download a youtube video and save it to your server and start streaming in your proper way in laravel.
I have made an image recognition system using python and I am trying to implement that in website. I have have a system that recognizes the fruit images built using CNN. Now, I have built a website which is of a Fruit-blog. I want a section or a page in in that website in which a user can upload an image and the website can recognize which fruit is the given image of but I have no idea how to implement my recognition system in the website. Can you please help me explaining what to do and how can I implement the AI from python to Django website?
The main part comes from freezing your model and serving it using a web framework like flask or django. Then you can communicate with it by passing images and receiving prediction objects. An example is at this github repo written in Django for deploy in Heroku https://github.com/marcogdepinto/Deep-learning-model-deploy-with-django
I have a python web project based on Pyramid. I have a confusion in deciding to use which tools I have to use to enable image uploading. I used pyramid_storage(https://github.com/danjac/pyramid_storage) to handle the image uploading before, but I haven't figured how to expire the uploaded file.
I am building am application to process user's photo on server. Basically, user upload a photo to the server and do some filtering processing using deep learning model. Once it's done filter, user can download the new photo. The filter program is based on the deep learning algorithm, using torch framework, it runs on python/lua. I currently run this filter code on my local ubuntu machine. Just wonder how to turn this into a web service. I have 0 server side knowledge, I did some research, maybe I should use flask or tornado, or other architecture?
I'd recommend using Django if you are comfortable with python and working with an AWS serviced database! It is pretty intuitive, and a lot of resources and examples are available on the web. For example, here is the file upload documentation.
It does make sense to look at the whole task and how it fits to your actual server, Nginx or Lighttpd or Apache since you are serving static content. If you are going to call a library to create the static content, the integration of your library to your web framework would be simpler if you use Flask but it might be a fit for AWS S3 and Lambda services.
It may be worth it to roughly design the whole site and match your content to the tools at hand.
Is there any library (or) application available in Python to support Video Streaming? It has to read the file and needs to stream over the web.
Check out Flumotion
It's a streaming media server implemented in Python.