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MLT Multimedia Framework

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Mirror of https://git.ffmpeg.org/ffmpeg.git

GStreamer open-source multimedia framework

OpenShot Video Library (libopenshot) is a free, open-source project dedicated to delivering high quality video editing, animation, and playback solutions to the world. API currently supports C++, Python, and Ruby.

Free and open source video editor, based on MLT Framework and KDE Frameworks

Quick Overview

MLT (Media Lovin' Toolkit) is an open-source multimedia framework designed for television broadcasting. It provides a toolkit for broadcasters, video editors, media players, transcoders, web streamers, and other types of media handling applications. MLT is flexible and supports a wide range of formats, making it suitable for various multimedia projects.

Pros

  • Supports a wide range of audio and video formats
  • Highly modular and extensible architecture
  • Cross-platform compatibility (Linux, macOS, Windows)
  • Integrates well with other multimedia tools and libraries

Cons

  • Steep learning curve for beginners
  • Documentation can be sparse or outdated in some areas
  • Limited community support compared to some other multimedia frameworks
  • Performance may not be optimal for high-end professional use cases

Code Examples

  1. Loading and playing a video file:
#include <mlt/framework/mlt_factory.h>
#include <mlt/framework/mlt_consumer.h>

int main() {
    mlt_profile profile = mlt_profile_init(NULL);
    mlt_producer producer = mlt_factory_producer(profile, NULL, "video.mp4");
    mlt_consumer consumer = mlt_factory_consumer(profile, "sdl", NULL);
    
    mlt_consumer_connect(consumer, mlt_producer_service(producer));
    mlt_consumer_start(consumer);
    mlt_consumer_wait_for_completed(consumer);
    
    mlt_consumer_close(consumer);
    mlt_producer_close(producer);
    mlt_profile_close(profile);
    return 0;
}
  1. Applying a filter to a video:
#include <mlt/framework/mlt_factory.h>
#include <mlt/framework/mlt_filter.h>

int main() {
    mlt_profile profile = mlt_profile_init(NULL);
    mlt_producer producer = mlt_factory_producer(profile, NULL, "video.mp4");
    mlt_filter filter = mlt_factory_filter(profile, "greyscale", NULL);
    
    mlt_producer_attach(producer, filter);
    
    // Further processing...
    
    mlt_filter_close(filter);
    mlt_producer_close(producer);
    mlt_profile_close(profile);
    return 0;
}
  1. Creating a simple transition between two videos:
#include <mlt/framework/mlt_factory.h>
#include <mlt/framework/mlt_playlist.h>
#include <mlt/framework/mlt_transition.h>

int main() {
    mlt_profile profile = mlt_profile_init(NULL);
    mlt_playlist playlist = mlt_playlist_init();
    mlt_producer video1 = mlt_factory_producer(profile, NULL, "video1.mp4");
    mlt_producer video2 = mlt_factory_producer(profile, NULL, "video2.mp4");
    mlt_transition transition = mlt_factory_transition(profile, "luma", NULL);
    
    mlt_playlist_append(playlist, video1);
    mlt_playlist_append(playlist, video2);
    mlt_playlist_mix(playlist, 1, 25, transition);
    
    // Further processing...
    
    mlt_transition_close(transition);
    mlt_producer_close(video2);
    mlt_producer_close(video1);
    mlt_playlist_close(playlist);
    mlt_profile_close(profile);
    return 0;
}

Getting Started

To get started with MLT:

  1. Install MLT and its dependencies:

    sudo apt-get install libmlt-dev melt
    
  2. Include the necessary headers in your C/C++ project:

    #include <mlt/framework/mlt_factory.h>
    #include <mlt/framework/mlt_producer.h>
    #include <mlt/framework/mlt_consumer.h>
    
  3. Compile

Competitor Comparisons

54,636

Mirror of https://git.ffmpeg.org/ffmpeg.git

Pros of FFmpeg

  • Broader functionality and support for a wider range of multimedia formats
  • Larger community and more extensive documentation
  • More frequent updates and active development

Cons of FFmpeg

  • Steeper learning curve for beginners
  • More complex command-line interface
  • Larger codebase, which can be overwhelming for some users

Code Comparison

FFmpeg example:

ffmpeg -i input.mp4 -vf scale=1280:720 -c:a copy output.mp4

MLT example:

melt input.mp4 -filter scale width=1280 height=720 -consumer avformat:output.mp4

Both examples demonstrate resizing a video to 720p resolution. FFmpeg uses a more concise syntax, while MLT employs a more verbose approach with separate filter and consumer options.

FFmpeg is a comprehensive multimedia framework with extensive capabilities for handling various audio and video tasks. It offers a powerful command-line interface and supports a wide range of formats and codecs. MLT, on the other hand, is a multimedia framework focused on video editing and production. It provides a simpler interface and is often used as a backend for video editing applications.

While FFmpeg excels in versatility and performance, MLT offers a more straightforward approach for specific video editing tasks. The choice between the two depends on the project requirements and the user's familiarity with each tool.

GStreamer open-source multimedia framework

Pros of GStreamer

  • Extensive plugin ecosystem with support for a wide range of multimedia formats and protocols
  • Strong community support and active development
  • Flexible pipeline architecture allowing complex multimedia processing

Cons of GStreamer

  • Steeper learning curve due to its complexity and extensive API
  • Can be resource-intensive for simple tasks
  • Debugging pipelines can be challenging for beginners

Code Comparison

MLT example:

producer = mlt.Producer(profile, "video.mp4")
consumer = mlt.Consumer(profile, "avformat", "output.mp4")
tractor = mlt.Tractor()
tractor.track(producer)
consumer.connect(tractor)
consumer.start()

GStreamer example:

pipeline = Gst.parse_launch("filesrc location=video.mp4 ! decodebin ! videoconvert ! x264enc ! mp4mux ! filesink location=output.mp4")
pipeline.set_state(Gst.State.PLAYING)

Both MLT and GStreamer are powerful multimedia frameworks, but they cater to different use cases. MLT is more focused on video editing and compositing, while GStreamer offers a broader range of multimedia processing capabilities. MLT's API is generally simpler and more intuitive for video editing tasks, whereas GStreamer provides more flexibility and extensibility for complex multimedia applications.

OpenShot Video Library (libopenshot) is a free, open-source project dedicated to delivering high quality video editing, animation, and playback solutions to the world. API currently supports C++, Python, and Ruby.

Pros of libopenshot

  • More modern C++ codebase with better object-oriented design
  • Extensive Python bindings for easier integration with Python projects
  • Built-in support for more video effects and transitions

Cons of libopenshot

  • Smaller community and less widespread adoption compared to MLT
  • Fewer supported input/output formats
  • Less mature and potentially less stable than MLT

Code Comparison

MLT (C):

mlt_producer producer = mlt_factory_producer(profile, "avformat", filename);
mlt_playlist playlist = mlt_playlist_new();
mlt_playlist_append(playlist, producer);

libopenshot (C++):

auto reader = std::make_shared<FFmpegReader>(filename);
auto clip = std::make_shared<Clip>(reader);
Timeline timeline(1280, 720, Fraction(24, 1));
timeline.AddClip(clip);

Both libraries provide APIs for loading media, creating timelines, and manipulating video content. MLT uses a more procedural approach with C-style functions, while libopenshot leverages modern C++ features and object-oriented design. libopenshot's API is generally more intuitive for developers familiar with object-oriented programming.

MLT has a longer history and wider adoption in the open-source video editing community, making it more battle-tested and potentially more stable. However, libopenshot's modern design and extensive Python bindings make it an attractive option for developers looking to integrate video editing capabilities into their projects, especially those working with Python.

Free and open source video editor, based on MLT Framework and KDE Frameworks

Pros of Kdenlive

  • User-friendly GUI for video editing, making it more accessible to non-technical users
  • Integrated with KDE applications and desktop environment for a seamless experience
  • Offers a wide range of video editing features and effects out-of-the-box

Cons of Kdenlive

  • Larger codebase and more complex architecture due to the GUI components
  • May have slower development cycles for core functionality updates
  • Potentially higher resource usage due to the graphical interface

Code Comparison

MLT (core functionality):

mlt_producer producer = mlt_factory_producer(profile, "avformat", filename);
mlt_playlist playlist = mlt_playlist_new();
mlt_playlist_append_io(playlist, producer, in, out);

Kdenlive (GUI interaction):

ClipController *clipController = new ClipController(url);
ProjectClip *clip = new ProjectClip(clipController, m_binModel);
m_binModel->addClip(clip);

Summary

MLT serves as a foundational framework for multimedia processing, while Kdenlive builds upon MLT to provide a full-featured video editing application with a graphical interface. MLT focuses on core functionality and is more suitable for developers and programmatic use, whereas Kdenlive caters to end-users looking for a complete video editing solution.

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README

MLT FRAMEWORK

MLT is a LGPL multimedia framework designed for video editing.

This document provides a quick reference for the minimal configuration, build and installation of MLT.

See the docs/ directory for usage details.

See the website for development details and a contributing guide.


Development Environment (Dev Container)

This repository provides a standardized development environment using the Development Containers specification. It is compatible with VS Code, CLion, DevPod, and other IDEs supporting the .devcontainer standard.

Prerequisites

  • Docker (or Podman)
  • An IDE with Dev Container support.

Hardware Acceleration and Audio Support

By default, the container runs in Restricted Mode (secure/headless). In this mode:

  • Audio is routed to a dummy driver (no sound).
  • GPU access might be limited to software rendering.

Enabling Real Hardware Access

To enable Full GPU Acceleration (DRI) and Physical Audio (ALSA/PulseAudio/PipeWire), follow these steps:

  1. Modify devcontainer.json: Uncomment the following lines inside the runArgs array:

    "--ipc=host",
    "--privileged"
    
    • What this does: --ipc=host allows shared memory access for high-performance video frames, and --privileged grants the container direct access to host devices (GPU nodes and Sound Cards).
  2. Trigger a Rebuild: Changes to runArgs require a container recreation.

    • In VS Code: Run the command Dev Containers: Rebuild Container.
    • In CLion: Select Restart and Rebuild Container.
  3. Switch the Audio Driver: The Dockerfile defaults to SDL_AUDIODRIVER=dummy. Once in privileged mode, you must tell the MLT consumer to use a real driver:

    • Temporary (CLI):
    SDL_AUDIODRIVER=alsa melt video.mp4
    
    • Permanent: Edit the ENV SDL_AUDIODRIVER line in your .devcontainer/Dockerfile to alsa or pulseaudio.

Warning: Using --privileged mode reduces the security isolation between the container and your host machine. Use it only when real-time hardware playback is required for development.


Configuration

Configuration is triggered by running CMake from inside a build directory, not from the project root.

mkdir -p build
cd build
cmake ..

Alternatively, you can configure CMake with Ninja:

cmake -G Ninja ..

More information on usage is found by viewing CMakeLists.txt and the CMake manual page.


Compilation

Once configured, it should be sufficient to run:

cmake --build .

Alternatively, you can compile with Ninja:

ninja

Alternatively, you can compile using CMake or Ninja with one less CPU core (recommended only on systems with many CPU cores):

cmake --build . --parallel $(($(nproc) - 1))
# or
ninja -j $(($(nproc) - 1))

All generated files (Makefiles, Ninja files, cache, object files, binaries) will remain inside the build/ directory.


Testing

To execute the MLT tools without installation, or to test a new version on a system with an already installed MLT version, run:

source ../setenv
ctest --output-on-failure # -j $(($(nproc) - 1))

NB:

  • This applies to the current shell only
  • It assumes a bash or Bourne-compatible shell is in use
  • The command must be executed from inside the build/ directory

Installation

Installation is triggered by running:

sudo cmake --install .

This installs the files generated in the build/ directory, without affecting the project source tree.

Note: After installation, some Linux systems may require running sudo ldconfig to refresh the shared library cache, especially if the install prefix is not already part of the system linker configuration.


Summary

mkdir build
cd build
cmake ..
cmake --build .
source ../setenv
ctest --output-on-failure
sudo cmake --install .

This approach keeps the source tree clean and allows the entire build to be removed safely by deleting the build/ directory.


More Information

For more detailed information, please refer to https://mltframework.org/docs/install/.