Hello I used to use Ubuntu a bunch a while ago and have recently transitioned back to the operating system, I've noticed that now Netflix only seems to show all their content in 540p with a low bitrate on Ubuntu on both Firefox and Chrome (I used the Ctrl+Alt+Shift+D command to check). So I was wondering if there is any way I can improve the quality I'm receiving, its quite ugly to watch to be honest. Thank you!
I have an 49XD8099 with Android 6.0.1. Simply put, to watch "The OA" from Netflix in HDR is unbearable. It's like if they added a wall of fog. Disabling the HDR the image improves considerably, still being a bit washed out. Other shows, when watched in HDR, don't look better either, so much that I decided to have a video mode with HDR off for Netflix only.
I must says that the HDR quality of various new Netflix videos quite improved. I am not sure if the Android TV updates and/or the fact that I watch Netflix via Apple TV 4K helped as well. So, to me it isn't a big issue anymore.
Secondly - im just going though a few posts that have been missed recently and found this one - Reading through, I am unsure on how to help you to be honest - other than suggesting that you choose the non-hdr version of OA
HDR on TVs that doesn't meet the HDR specifications will always look awful and never will be HDR. Just like DD with just 2 speakers is not exactly a DD. And the idea of marketing TVs as HDR while they are not is just a bad idea. Sure, they can process HDR signal but display can't reproduce it in a way that it should look.
I believe it is possible on some 4K HDR content on Netfix.... Or was it Amazon, im now unsure. Basically you could choose the 1080p version over 4K HDR version instead due to it being in another category. I did it not long ago.
I couldn't find any way for Netflix. It is also not possible on a system level to disable HDR. At least not for ATV1. Maybe @Jecht_Sin or someone else has an idea how to achieve that. I think on ATV2 there is an option, see above quote and link to FlatpanelsHD.
The quality standards that is followed by netflix is just great and appreciate teh type of contetn being posted on their sites!!! thumbs up. [Link removed by moderator] is also similar to netflix where one can watch movies,cartoons,daily soaps anytime they feel like.!!
- After posting this I had a chat with Netflix, and no, there are no options to disable HDR in the player. The most one can do, from the settings in the web browser, is to reduce the available bandwidth, so that it will stream at 1080p. - The other option is to simply disable the HDR in the settings for a channel, but that disables it everywhere.
Still the issue is mostly with "The OA" (which I could just avoid watching for this reason and for the other more important reason that it is a stupid show. What a waste of time). Other HDR videos in Netflix look much better, and "Grand Tour" in Amazon looks amazing. So do the HDR demo downloaded from the internet at full bit rates (and they look awful with HDR disabled).
I must also say that Netflix streaming quality, in my opinion, can be disappointing. Many UHD videos look granulated. I have a fiber connection so it isn't a bandwidth issue. I am honestly a bit surprised. Even Youtube videos look better!
Sorry, sometime the English words flips in my brain. I meant an image mode. Then I have got also confused with the inputs (like HDMI 2 vs App (Video) ). Anyway, from Android changing the HDR to NO in a image mode (like custom) it puts HDR NO in all modes.
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Over 69 million Netflix members stream billions of hours of movies and shows every month in North and South America, parts of Europe and Asia, Australia and New Zealand. Soon, Netflix will be available in every corner of the world with an even more global member base.
As we expand globally, our goal is to ensure that every member has a high-quality experience every time they stream content on Netflix. This challenging problem is impacted by factors that include quality of the member's Internet connection, device characteristics, content delivery network, algorithms on the device, and quality of content.
We previously looked at opportunities to improve the Netflix streaming experience using data science. In this post, we'll focus on predictive modeling to optimize the quality control (QC) process for content at Netflix.
Imagine sitting down to watch the first episode of a new season of your favorite show, only to find that the video and audio are off by 20 seconds. You decide to watch it anyway and turn on subtitles to follow along. What if the subtitles are poorly positioned and run off the screen?
We receive assets either from the content owners (e.g. studios, documentary filmmakers) or from a fulfillment house that obtains content from the owners and packages the assets for delivery to Netflix. Our QC process consists of automated and manual inspections to identify and replace assets that do not meet our specified quality standards.
We looked at the data on manual QC failures and observed that certain factors affected the likelihood of an asset failing QC. For example, some combinations of content and fulfillment partners had a higher rate of defects for certain types of assets. Metadata related to the content also showed patterns of failure. For example, older content (by release year) had a higher defect rate, likely due to the use of older formats for the creation and storage of assets. The genre of the content also exhibited certain patterns of failure.
A key goal of the model is to identify all defective assets even if this results in extra manual checks. Hence, we tuned the model for low false-negative rate (i.e. fewer uncaught defects) at the cost of increased false-positive rate.
We performed offline validation of the model by passively making predictions on incoming assets and comparing with actual results from manual QC. This allowed us to fine tune the model parameters and validate the model before deploying into production. Offline validation also confirmed the scaling and quality improvement benefits outlined earlier.
But do these pricier plans actually improve the quality of video streaming? A Wall Street Journal investigation recently answered this question with the help of Prof. Nick Feamster, a University of Chicago expert on the performance and security of communications networks, in a collaboration that both informs consumers and advances science.
While video providers such as Netflix, Amazon and YouTube can collect data on the quality that users receive through their software, ISPs and outside researchers are in the dark. With the help of the Wall Street Journal, the researchers recruited more than 60 households, collected information about their internet service, and installed a monitor of the data passing through their network. But challenges remained.
The work led to a research paper and a new tool called Net Microscope, which infers video streaming quality metrics such as startup delay and resolution in real time from the encrypted data stream. By gathering data from more than 200,000 video sessions from the volunteer homes, the team trained a model that that can look at encrypted data and identify which streams are from Netflix, YouTube, Amazon and Twitch, as well as the quality that end users experience.
From there, the researchers could finally answer the question posed by the Wall Street Journal : How do these services perform at different internet speeds? The study found that streaming video performance plateaus long before the upper-tier plans offered by ISPs, with plans above 100 megabits-per-second only marginally improving startup delays and resolution, even when multiple devices are viewing videos simultaneously.
Like the Wall Street Journal project, many of these research areas and policy issues require creating new software and systems that can collect data and measure performance in the real world. From the lens of his new role at the Center for Data and Computing, Feamster sees this project as the beginning of what he hopes will be more work at the intersection of data science, public policy and investigative journalism.
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Subtitles are onscreen text that typically represent spoken dialogue, but can also encompass pertinent information such as music playing in closed captioning for the hearing impaired. In brief: Subtitles provide access to video content that is otherwise inaccessible.
Transcription: The first step in subtitling is transcription, either using a script, transcribing manually, or using an automated tool such as Premiere Pro (I cover the Premiere Pro workflow in my on-demand course Subtitling for Streaming.)
Spotting: When you have a transcript, you can use Premiere Pro to create an initial round of subtitles, or you can manually take the transcript and perform spotting in a subtitling tool such as VisualSubSync Enhanced or Subtitle Edit. Spotting is basically chunking up the transcript and fitting it to a timeline. While you can use Premiere Pro for automated captions, my course covers how to use VisualSubSync Enhanced. This tool has built-in quality assurance to perform post-processing on Premiere auto-generated subtitles to shape them into compliance.
The default setting will enable you to stream about 3 hours of TV shows and movies per gigabyte of data. In terms of bitrates, that currently amounts to about 600 Kilobits per second. Our testing found that, on cellular networks, this setting balances good video quality with lower data usage to help avoid exceeding data caps and incurring overage fees
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