FolhaSP / mosaico

🎬 Open-source programmatic video composition framework with AI capabilities for Python
https://folhasp.github.io/mosaico/
GNU General Public License v3.0
6 stars 0 forks source link
ai artificial-intelligence content-generation media-processing python script-writing speech-synthesis text-to-speech timeline video video-automation video-composition video-editing video-generation video-processing

Mosaico

License Python PyPI Downloads Stars

Mosaico is a Python library for programmatically creating and managing video compositions. It provides a high-level interface for working with media assets, positioning elements, applying effects, and generating video scripts.

Installation

pip install mosaico

For additional dependencies, see the additional dependencies section in the documentation.

Features

Quick Start

Install Mosaico and additional dependencies for news video generation:

pip install "mosaico[news,assemblyai,elevenlabs]"

Easily create and render a video project from a script generator:

import os

from mosaico.audio_transcribers.assemblyai import AssemblyAIAudioTranscriber
from mosaico.script_generators.news import NewsVideoScriptGenerator
from mosaico.speech_synthesizers.elevenlabs import ElevenLabsSpeechSynthesizer
from mosaico.video.project import VideoProject
from mosaico.video.rendering import render_video

# Set your API keys
ANTHROPIC_API_KEY = os.getenv("ANTHROPIC_API_KEY")
ASSEMBLYAI_API_KEY = os.getenv("ASSEMBLYAI_API_KEY")
ELEVENLABS_API_KEY = os.getenv("ELEVENLABS_API_KEY")

# Import your media
media = [
    Media.from_path("background.jpg", metadata={"description": "Background image"}),
    Media.from_path("image1.jpg", metadata={"description": "Image 1"}),
    Media.from_path("image2.jpg", metadata={"description": "Image 2"}),
    Media.from_path("image3.jpg", metadata={"description": "Image 3"}),
]

# Textual context for the video
context = "..."

# Create script generator
script_generator = NewsVideoScriptGenerator(
    context=context,
    language="pt",
    num_paragraphs=8,
    api_key=ANTHROPIC_API_KEY,
)

# Create speech synthesizer
speech_synthesizer = ElevenLabsSpeechSynthesizer(
    voice_id="Xb7hH8MSUJpSbSDYk0k2",
    voice_stability=0.8,
    voice_similarity_boost=0.75,
    voice_speaker_boost=False,
    api_key=ELEVENLABS_API_KEY,
)

# Create audio transcriber for captions
audio_transcriber = AssemblyAIAudioTranscriber(api_key=ASSEMBLYAI_API_KEY)

# Create project
project = (
    VideoProject.from_script_generator(script_generator, media)
    .with_title("My Breaking News Video")
    .with_fps(30)
    .with_resolution((1920, 1080))
    .add_narration(speech_synthesizer)
    .add_captions_from_transcriber(audio_transcriber, overwrite=True)
)

# Render project
render_video(project, "path/to/dir")

Or create a video project from scratch:

from mosaico.video.project import VideoProject
from mosaico.assets import ImageAsset, TextAsset, AudioAsset, AssetReference

# Import your media as production-ready assets
assets = [
    ImageAsset.from_path("background.jpg", metadata={"description": "Background image"}),
    ImageAsset.from_path("image1.jpg", metadata={"description": "Image 1"}),
    ImageAsset.from_path("image2.jpg", metadata={"description": "Image 2"}),
    ImageAsset.from_path("image3.jpg", metadata={"description": "Image 3"}),
    TextAsset.from_data("Subtitle 1"),
    TextAsset.from_data("Subtitle 2"),
    TextAsset.from_data("Subtitle 3"),
    AudioAsset.from_path("narration.mp3"),
]

asset_references = [
    AssetReference.from_asset(background, start_time=0, end_time=10),
    AssetReference.from_asset(image1, start_time=10, end_time=20),
    AssetReference.from_asset(image2, start_time=20, end_time=30),
    AssetReference.from_asset(image3, start_time=30, end_time=40),
    AssetReference.from_asset(subtitle1, start_time=40, end_time=50),
    AssetReference.from_asset(subtitle2, start_time=50, end_time=60),
    AssetReference.from_asset(subtitle3, start_time=60, end_time=70),
    AssetReference.from_asset(narration, start_time=70, end_time=80),
]

scene = Scene(description="My Scene").add_asset_references(asset_references)

project = (
    VideoProject()
    .with_title("My Breaking News Video")
    .with_fps(30)
    .with_resolution((1920, 1080))
    .add_assets(assets)
    # Add the asset references as scene events to the timeline
    .add_timeline_events(scene)
    # Or add asset references directly to the timeline
    # .add_timeline_events(asset_references)
)

# Render project
render_video(project, "path/to/dir")

Cookbook

For common usage patterns and examples, see our Cookbook. Some examples include:

Documentation

Comprehensive documentation is available here. Documentation includes:

References