drm | Direct Rendering Manager in pure Go | Graphics library

 by   NeowayLabs Go Version: Current License: No License

kandi X-RAY | drm Summary

kandi X-RAY | drm Summary

drm is a Go library typically used in User Interface, Graphics applications. drm has no bugs, it has no vulnerabilities and it has low support. You can download it from GitHub.

The Direct Rendering Manager (DRM) is a kernel framework to manage Graphical Processing Units (GPU). It's a kernel abstractions to GPU drivers and a userspace API designed to support the needs of complex graphics devices. DRM was first implemented on Linux but ported to FreeBSD, NetBSD and Solaris (others?). It's the lower level interface between opengl and the graphics card. With this Go library, theoretically, now it's possible to create a X server or a pure OpenGL library in Go (no bindings).
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            kandi-support Support

              drm has a low active ecosystem.
              It has 29 star(s) with 12 fork(s). There are 2 watchers for this library.
              OutlinedDot
              It had no major release in the last 6 months.
              drm has no issues reported. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of drm is current.

            kandi-Quality Quality

              drm has 0 bugs and 0 code smells.

            kandi-Security Security

              drm has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              drm code analysis shows 0 unresolved vulnerabilities.
              There are 0 security hotspots that need review.

            kandi-License License

              drm does not have a standard license declared.
              Check the repository for any license declaration and review the terms closely.
              OutlinedDot
              Without a license, all rights are reserved, and you cannot use the library in your applications.

            kandi-Reuse Reuse

              drm releases are not available. You will need to build from source code and install.
              It has 1419 lines of code, 53 functions and 15 files.
              It has high code complexity. Code complexity directly impacts maintainability of the code.

            Top functions reviewed by kandi - BETA

            kandi has reviewed drm and discovered the below as its top functions. This is intended to give you an instant insight into drm implemented functionality, and help decide if they suit your requirements.
            • findCrtc finds an encoders matching the connector
            • GetConnector gets a connector .
            • Main entry point .
            • GetVersion reads version information from file
            • GetResources retrieves system resources from a file .
            • draw generates a random number of mset data .
            • createFramebuffer creates a new framebuffer .
            • ListDevices returns a list of all available devices .
            • destroyFramebuffer destroys a framebuffer
            • GetCrtc retrieves a row from a file .
            Get all kandi verified functions for this library.

            drm Key Features

            No Key Features are available at this moment for drm.

            drm Examples and Code Snippets

            No Code Snippets are available at this moment for drm.

            Community Discussions

            QUESTION

            ffmpeg copy codec outputs in slowmotion
            Asked 2022-Apr-08 at 00:16

            i have the following scenario that is driving me crazy:

            i have a capture device. Here the ffprobe on it:

            ...

            ANSWER

            Answered 2022-Apr-08 at 00:16

            *.mjpeg is a raw stream format. FFmpeg documentation states of raw muxers: "They do not store timestamps or metadata." So, instead try storing the data in an mp4 container:

            Source https://stackoverflow.com/questions/71783986

            QUESTION

            Azure Media Services v2 to v3 Upgrade - Custom Key Delivery Service: how to provide Clear Key Value
            Asked 2022-Apr-04 at 19:06

            I am trying to upgrade an Azure Media Services v2 implementation to v3 which uses a Custom Key Delivery Service mentioned here to v3. Other than this section and samples from the REST API section, I have found this to be largely undocumented but I believe I have figured out mostly everything, however on the actual Delivery of the Key I am wondering if the format I am returning is in the correct format (I cannot find this easily anywhere). It seems that the Video Player is not working even though I see the request come through and getting sent back out.

            Do I return the key in ByteArray format as seen in my v3 example below?

            Media Services v2 Implementation

            ...

            ANSWER

            Answered 2022-Apr-04 at 19:06

            Many thanks to @Sanjid above, here is the working solution (tested with a Client Side Video Player).

            Source https://stackoverflow.com/questions/71669251

            QUESTION

            How to fix "NVRM: API mismatch" between client version and kernel module version when installing Nvidia drivers for a GTX 560 Ti in Ubuntu 20.04?
            Asked 2022-Apr-03 at 18:54

            I have installed nvidia-driver-390 after adding a GTX 560 Ti on an Intel Core i5 12600K PC running Kubuntu 20.04 LTS.

            After rebooting I get the following error:

            ...

            ANSWER

            Answered 2021-Dec-13 at 16:51

            I found the solution and now Kubuntu starts up normally as expected.

            First, I purged all drivers and libraries

            Source https://stackoverflow.com/questions/70276412

            QUESTION

            softlockup with dpdk 19 mellanox connectx5
            Asked 2022-Apr-03 at 08:42

            I have server with centos 7.9 3.10.0-1160.53.1.el7.x86_64

            When running my dpdk 19 muliple process application i have softlockup

            The server i run on have 2 ixgbe 10G, and one 100G connectx-5

            ...

            ANSWER

            Answered 2022-Apr-03 at 08:42

            Adding iommu=pt intel_iommu=on to the grub solve the softlockup and the 10 G Rx

            Source https://stackoverflow.com/questions/71018338

            QUESTION

            Use data.table instead of pivot_longer
            Asked 2022-Mar-31 at 22:27

            I would like some help to adjust the output called adjusted that I generate. My idea is to optimize somehow to generate faster. Notice that I'm using pivot_longer, which takes longer. One idea would be to continue using data.table as I did to generate SPV. However, I don't know how to do that in this case for adjusted. Can you help me?

            I would like to generate the same output table as in the question.

            ...

            ANSWER

            Answered 2022-Mar-31 at 22:22

            With data.table, use melt after doing the filtering and grouping

            Source https://stackoverflow.com/questions/71699631

            QUESTION

            Use different approach than inner_join
            Asked 2022-Mar-31 at 17:07

            I would like to use another resolution approach that is faster to calculate the SPV. See that I use inner_join, which is a function that takes considerable computational time, so there is another way to calculate the SPV, other than inner_join and make it faster.?

            ...

            ANSWER

            Answered 2022-Mar-31 at 17:07

            As we are using data.table, data.table join could be faster

            Source https://stackoverflow.com/questions/71696135

            QUESTION

            Play m3u8 or mpd file videos offline
            Asked 2022-Mar-31 at 13:57

            I get m3u8 or mpd file from server and i download it in my app storage. How will i play it offline. Im newbie to offline videos. Any suggestion for its usage methods. Currently i play m3u8 or mpd files with exoplayer which is Dash, HLS or progressive videos. How to play these videos offline by keeping allrights drm in mind.

            ...

            ANSWER

            Answered 2021-Sep-17 at 16:11

            The mpd or m3u8 files are just manifests or index files. They are text based containing information about the video and links to the media, i.e. the audio, video, subtitles etc streams.

            If you want to download a HLS or DASH stream for offline playback, you will need to download the manifest and the media streams they refer to.

            ExoPlayer provides functionality to help you download video and take care of much of this complexity, including specific information on downloading HLS and DASH videos - see the ExoPlayer documentation:

            Note the section around tracks selection and bit rates - typically you will want to choose a particular bitrate to download rather than downloading all available ones:

            For streaming playbacks, a track selector can be used to choose which of the tracks are played. Similarly, for downloading, a DownloadHelper can be used to choose which of the tracks are downloaded.

            To support encrypted streams you need to ensure that the DRM server supports persistent licenses for that content and the entitlements allow offline playback - you will generally need to speak to your DRM provider to confirm this.

            Source https://stackoverflow.com/questions/69102812

            QUESTION

            Can NAN and INFINITY be used under non-default rounding modes?
            Asked 2022-Mar-26 at 18:37

            Sample code:

            ...

            ANSWER

            Answered 2022-Jan-14 at 23:05

            is it allowed at all to use NAN and INFINITY under non-default rounding modes, such as FE_TOWARDZERO and FE_DOWNWARD?

            The language specification does not express any limitation on using INFINITY. A conforming implementation must therefore accept it and interpret it consistently with the provisions of the language specification regardless of rounding mode. Specifically, it

            expands to a constant expression of type float representing positive or unsigned infinity, if available; else to a positive constant of type float that overflows at translation time.

            (C17 7.12/4)

            That is not conditioned on the rounding mode in effect at any particular time. Since MSVC does have an available float representation for infinity and FLT_MAX is required to be a representation of a finite number, it is non-conforming for INFINITY to evaluate equal to FLT_MAX in MSVC, under any circumstances. Indeed, MSVC is non-conforming to whatever extent INFINITY ever fails to evaluate to a positive float infinity.

            It is even more clear for NAN. The specification says that it

            is defined if and only if the implementation supports quiet NaNs for the float type.

            In that case,

            It expands to a constant expression of type float representing a quiet NaN.

            (C17 7.12/5)

            If NAN is defined at all then it expands to an expression that evaluates to a quiet NaN. Period. If MSVC provides for circumstances in which it instead expands to 0.0, then MSVC is non-conforming under those circumstances.

            It should be acknowledged that most, if not all, C implementations have some non-conformity, whether by default or accessible via command-line options or similar. Nevertheless, MSVC is notorious for its comparatively poor conformance among the widely used C implementations.

            Source https://stackoverflow.com/questions/70717240

            QUESTION

            How to adjust function without specifying dataset
            Asked 2022-Mar-24 at 20:56

            I have a function that basically filters an SPV row, as you can see below. Note that I do return_coef <- function(df1, idd,dmda, CategoryChosse) { However, I would not like df1 as an argument of the function, but rather the attributes of the df1 dataset, which in this case is Id, date1, Week, Category, DR1 and DRM. How can I adjust this?

            ...

            ANSWER

            Answered 2022-Mar-21 at 14:06

            I think what you want is to be able to specify arbitrary columns from a dataframe to be used as Id, date1, Week, etc inside return_coef(), rather than having to use a dataframe that already has those specific column names. If so, you can use the tidyeval embracing operator, {{.

            Source https://stackoverflow.com/questions/71528512

            QUESTION

            How to get predictions from multiple fitted models
            Asked 2022-Mar-08 at 11:14

            I have a data frame with calibration curves for multiple samples (signal s as a function of concentration c):

            ...

            ANSWER

            Answered 2022-Mar-07 at 22:43
            cal <- data.frame(sample = c(rep("A", 8), rep("B", 8), rep("C", 8)),
                              c_std = rep(c(0, 1, 5, 10, 25, 50, 100, 200), 3),
                              s_std = c(40341, 24196, 13403,  6956,  3000,  1507, 312, 12,
                                        40261, 24250, 13537,  6977,  2940,  1465, 304, 12,
                                        40075, 24469, 13696,  7060,  2972,  1487, 307, 12))
            obs <- data.frame(sample = c("A", "B", "C"),
                              s_std = c(1364, 4726, 521))
            library(purrr)
            library(dplyr)
            #> 
            #> Attaching package: 'dplyr'
            #> The following objects are masked from 'package:stats':
            #> 
            #>     filter, lag
            #> The following objects are masked from 'package:base':
            #> 
            #>     intersect, setdiff, setequal, union
            library(tidyr)
            setNames(predict(drc::drm(c_std ~ s_std, fct = drc::LL2.3(), data = cal), obs), obs$sample)
            #>        A        B        C 
            #> 44.78515 18.20520 79.81111
            cal %>%
                group_by(sample) %>%
                nest() %>%
                mutate(
                    model = map(data, ~drc::drm(c_std ~ s_std, fct = drc::LL2.3(), data = .x)),
                    pred = map2(model, sample, ~predict(.x, filter(obs, sample == .y)))
                ) %>%
                unnest(pred)
            #> # A tibble: 3 x 4
            #> # Groups:   sample [3]
            #>   sample data             model   pred
            #>                 
            #> 1 A          45.1
            #> 2 B          18.1
            #> 3 C          79.8
            

            Source https://stackoverflow.com/questions/71387438

            Community Discussions, Code Snippets contain sources that include Stack Exchange Network

            Vulnerabilities

            No vulnerabilities reported

            Install drm

            You can download it from GitHub.

            Support

            For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .
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            gh repo clone NeowayLabs/drm

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            git@github.com:NeowayLabs/drm.git

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