movis

movis

Python视频编辑引擎让视频创作如代码编写般简洁

Movis是一款Python编写的视频制作引擎,支持通过代码生成演示视频、动态图形和游戏评论等多种视频类型。它提供图层变换、混合模式、关键帧动画和嵌套合成等高级功能,具备直观的编辑界面,满足从简单到复杂的各类视频编辑需求,是一个功能全面且易用的视频制作工具。

Movis视频编辑Python库代码创作动画引擎Github开源项目

GitHub Logo

Movis: Video Editing as a Code

Python pypi GitHub license Continuous integration Docs

Docs | Overview | Install Guide | Examples | API Reference | Contribution Guide

✅ What is Movis?

Movis is an engine written in Python, purposed for video production tasks. This library allows users to generate various types of videos, including but not limited to presentation videos, motion graphics, shader art coding, and game commentary videos, through Python.

Open In Colab

🚀 Main Features

  • Easy and intuitive video editing (including scene cut, transition, crop, concatenation, inserting images and texts, etc.)
  • Inserting text layers containing multiple outlines
  • Simple audio editing (including fade-in and fade-out effects)
  • Support for a variety of video and audio formats using ffmpeg

The following features are not found in other Python libraries for video editing:

  • Layer transformation (position, scale, and rotation) with sub-pixel precision
  • Support for a variety of Photoshop-level blending modes
  • Keypoint and easing-based animation engine
  • Nested compositions
  • Support for rendering at 1/2 quality and 1/4 quality for drafts
  • Fast rendering using cache mechanism
  • Adding user-defined layers, effects, and animations without using inheritance
  • Layer effects (drop shadow, grow, blur, chromakey, etc.)

To put it simply, Movis is a library for complex video editing that includes several features found in proprietary software.

💻 Installation

Movis is a pure Python library and can be installed via the Python Package Index:

$ pip install movis

We have confirmed that it works with Python 3.9 to 3.11.

⭐️ Code Overview

Creating Video with Compositions

Similar to other video editing software, Movis employs the concept of "compositions" as the fundamental unit for video editing. Within a composition, users can include multiple layers and manipulate these layers' attributes over a time scale to produce a video. Effects can also be selectively applied to these layers as needed.

Here's some example code:

import movis as mv scene = mv.layer.Composition(size=(1920, 1080), duration=5.0) scene.add_layer(mv.layer.Rectangle(scene.size, color='#fb4562')) # Set background pos = scene.size[0] // 2, scene.size[1] // 2 scene.add_layer( mv.layer.Text('Hello World!', font_size=256, font_family='Helvetica', color='#ffffff'), name='text', # The layer item can be accessed by name offset=1.0, # Show the text after one second position=pos, # The layer is centered by default, but it can also be specified explicitly anchor_point=(0.0, 0.0), opacity=1.0, scale=1.0, rotation=0.0, # anchor point, opacity, scale, and rotation are also supported blending_mode='normal') # Blending mode can be specified for each layer. scene['text'].add_effect(mv.effect.DropShadow(offset=10.0)) # Multiple effects can be added. scene['text'].scale.enable_motion().extend( keyframes=[0.0, 1.0], values=[0.0, 1.0], easings=['ease_in_out']) # Fade-in effect. It means that the text appears fully two seconds later. scene['text'].opacity.enable_motion().extend([0.0, 1.0], [0.0, 1.0]) scene.write_video('output.mp4')

The composition can also be used as a layer. By combining multiple compositions and layers, users can create complex videos.

scene2 = mv.layer.Composition(scene.size, duration=scene.duration) layer_item = scene2.add_layer(scene, name='scene') # Equivalent to scene2['scene'].add_effect(...) layer_item.add_effect(mv.effect.GaussianBlur(radius=10.0))

Simple video processing

Of course, movis also supports simple video processing such as video merging and trimming.

concat

intro = mv.layer.Video('intro.mp4') title = mv.layer.Video('title.mp4') chapter1 = mv.layer.Composition(size=(1920, 1080), duration=60.0) ... main = mv.concatenate([intro, title, chapter1, ...])

cutout

raw_video = mv.layer.Video('video.mp4') # select 0.0-1.0 secs and 2.0-3.0 secs, and concatenate them video = mv.trim(raw_video, start_times=[0.0, 2.0], end_times=[1.0, 3.0])

cropping

layer = mv.layer.Image("image.png", duration=1.0) # crop from x, y = (10, 20) with size w, h = (100, 200) layer = mv.crop(layer, (10, 20, 100, 200))

resizing

layer = mv.layer.Video('video.mp4') width, height = layer.size # resize to 1/2 main = mv.layer.Composition(size=(width // 2, height // 2), duration=layer.duration) main.add_layer(layer, scale=0.5)

fade-in / out

layer = mv.layer.Video('video.mp4') video1 = mv.fade_in(layer, 1.0) # fade-in for 1.0 secs video2 = mv.fade_out(layer, 1.0) # fade-out for 1.0 secs video3 = mv.fade_in_out(layer, 1.0, 2.0) # fade-in for 1.0 secs and fade-out for 2.0 secs

Implementation of custom layers, effects, and animations

Movis is designed to make it easy for users to implement custom layers and effects. This means that engineers can easily integrate their preferred visual effects and animations using Python.

For example, let's say you want to create a demo video using your own machine learning model for tasks like anonymizing face images or segmenting videos. With Movis, you can easily do this without the need for more complex languages like C++, by directly using popular libraries such as PyTorch or Jax. Additionally, for videos that make use of GPGPU like shader art, you can implement these intuitively through Python libraries like Jax or cupy.

For example, to implement a user-defined layer, you only need to create a function that, given a time, returns an np.ndarray with a shape of (H, W, 4) and dtype of np.uint8 in RGBA order, or returns None.

import numpy as np import movis as mv size = (640, 480) def get_radial_gradient_image(time: float) -> np.ndarray: center = np.array([size[1] // 2, size[0] // 2]) radius = min(size) inds = np.mgrid[:size[1], :size[0]] - center[:, None, None] r = np.sqrt((inds ** 2).sum(axis=0)) p = 255 - (np.clip(r / radius, 0, 1) * 255).astype(np.uint8) img = np.zeros((size[1], size[0], 4), dtype=np.uint8) img[:, :, :3] = p[:, :, None] img[:, :, 3] = 255 return img scene = mv.layer.Composition(size, duration=5.0) scene.add_layer(get_radial_gradient_image) scene.write_video('output.mp4')

If you want to specify the duration of a layer, the duration property is required. Movis also offers caching features to accelerate rendering. If you wish to speed up rendering for layers where the frame remains static, you can implement the get_key(time: float) method:

class RadialGradientLayer: def __init__(self, size: tuple[int, int], duration: float): self.size = size self.duration = duration self.center = np.array([size[1] // 2, size[0] // 2]) def get_key(self, time: float) -> Hashable: # Returns 1 since the same image is always returned return 1 def __call__(self, time: float) -> None | np.ndarray: # ditto.

Custom effects

Effects for layers can also be implemented in a similar straightforward manner.

import cv2 import movis as mv import numpy as np def apply_gaussian_blur(prev_image: np.ndarray, time: float) -> np.ndarray: return cv2.GaussianBlur(prev_image, (7, 7), -1) scene = mv.layer.Composition(size=(1920, 1080), duration=5.0) scene.add_layer(mv.layer.Rectangle(scene.size, color='#fb4562')) scene.add_layer( mv.layer.Text('Hello World!', font_size=256, font_family='Helvetica', color='#ffffff'), name='text') scene['text'].add_effect(apply_gaussian_blur)

User-defined animations

Animation can be set up on a keyframe basis, but in some cases, users may want to animate using user-defined functions. movis provides methods to handle such situations as well.

import movis as mv import numpy as np scene = mv.layer.Composition(size=(1920, 1080), duration=5.0) scene.add_layer( mv.layer.Text('Hello World!', font_size=256, font_family='Helvetica', color='#ffffff'), name='text') scene['text'].position.add_function( lambda prev_value, time: prev_value + np.array([0, np.sin(time * 2 * np.pi) * 100]), )

Fast Prototyping on Jupyter Notebook

Jupyter notebooks are commonly used for data analysis that requires a lot of trial and error using Python. Some methods for Jupyter notebooks are also included in movis to speed up the video production process.

For example, composition.render_and_play() is often used to preview a section of a video within a Jupyter notebook.

import movis as mv scene = mv.layer.Composition(size=(1920, 1080), duration=10.0) ... # add layers and effects... scene.render_and_play( start_time=5.0, end_time=10.0, preview_level=2) # play the video from 5 to 10 seconds

This method has an argument called preview_level. For example, by setting it to 2, you can sacrifice video quality by reducing the final resolution to 1/2 in exchange for faster rendering.

If you want to reduce the resolution when exporting videos or still images using composition.write_video() or similar methods, you can use the syntax with composition.preview(level=2).

import movis as mv scene = mv.layer.Composition(size=(1920, 1080), duration=10.0) ... # add layers and effects... with scene.preview(level=2): scene.write_video('output.mp4') # The resolution of the output video is 1/2. img = scene(5.0) # retrieve an image at t = 5.0 assert img.shape == (540, 960, 4)

Within this scope, the resolution of all videos and images will be reduced to 1/2. This can be useful during the trial and error process.

📃 License

MIT License (see LICENSE for details).

编辑推荐精选

Trae

Trae

字节跳动发布的AI编程神器IDE

Trae是一种自适应的集成开发环境(IDE),通过自动化和多元协作改变开发流程。利用Trae,团队能够更快速、精确地编写和部署代码,从而提高编程效率和项目交付速度。Trae具备上下文感知和代码自动完成功能,是提升开发效率的理想工具。

AI工具TraeAI IDE协作生产力转型热门
蛙蛙写作

蛙蛙写作

AI小说写作助手,一站式润色、改写、扩写

蛙蛙写作—国内先进的AI写作平台,涵盖小说、学术、社交媒体等多场景。提供续写、改写、润色等功能,助力创作者高效优化写作流程。界面简洁,功能全面,适合各类写作者提升内容品质和工作效率。

AI辅助写作AI工具蛙蛙写作AI写作工具学术助手办公助手营销助手AI助手
问小白

问小白

全能AI智能助手,随时解答生活与工作的多样问题

问小白,由元石科技研发的AI智能助手,快速准确地解答各种生活和工作问题,包括但不限于搜索、规划和社交互动,帮助用户在日常生活中提高效率,轻松管理个人事务。

热门AI助手AI对话AI工具聊天机器人
Transly

Transly

实时语音翻译/同声传译工具

Transly是一个多场景的AI大语言模型驱动的同声传译、专业翻译助手,它拥有超精准的音频识别翻译能力,几乎零延迟的使用体验和支持多国语言可以让你带它走遍全球,无论你是留学生、商务人士、韩剧美剧爱好者,还是出国游玩、多国会议、跨国追星等等,都可以满足你所有需要同传的场景需求,线上线下通用,扫除语言障碍,让全世界的语言交流不再有国界。

讯飞智文

讯飞智文

一键生成PPT和Word,让学习生活更轻松

讯飞智文是一个利用 AI 技术的项目,能够帮助用户生成 PPT 以及各类文档。无论是商业领域的市场分析报告、年度目标制定,还是学生群体的职业生涯规划、实习避坑指南,亦或是活动策划、旅游攻略等内容,它都能提供支持,帮助用户精准表达,轻松呈现各种信息。

AI办公办公工具AI工具讯飞智文AI在线生成PPTAI撰写助手多语种文档生成AI自动配图热门
讯飞星火

讯飞星火

深度推理能力全新升级,全面对标OpenAI o1

科大讯飞的星火大模型,支持语言理解、知识问答和文本创作等多功能,适用于多种文件和业务场景,提升办公和日常生活的效率。讯飞星火是一个提供丰富智能服务的平台,涵盖科技资讯、图像创作、写作辅助、编程解答、科研文献解读等功能,能为不同需求的用户提供便捷高效的帮助,助力用户轻松获取信息、解决问题,满足多样化使用场景。

热门AI开发模型训练AI工具讯飞星火大模型智能问答内容创作多语种支持智慧生活
Spark-TTS

Spark-TTS

一种基于大语言模型的高效单流解耦语音令牌文本到语音合成模型

Spark-TTS 是一个基于 PyTorch 的开源文本到语音合成项目,由多个知名机构联合参与。该项目提供了高效的 LLM(大语言模型)驱动的语音合成方案,支持语音克隆和语音创建功能,可通过命令行界面(CLI)和 Web UI 两种方式使用。用户可以根据需求调整语音的性别、音高、速度等参数,生成高质量的语音。该项目适用于多种场景,如有声读物制作、智能语音助手开发等。

咔片PPT

咔片PPT

AI助力,做PPT更简单!

咔片是一款轻量化在线演示设计工具,借助 AI 技术,实现从内容生成到智能设计的一站式 PPT 制作服务。支持多种文档格式导入生成 PPT,提供海量模板、智能美化、素材替换等功能,适用于销售、教师、学生等各类人群,能高效制作出高品质 PPT,满足不同场景演示需求。

讯飞绘文

讯飞绘文

选题、配图、成文,一站式创作,让内容运营更高效

讯飞绘文,一个AI集成平台,支持写作、选题、配图、排版和发布。高效生成适用于各类媒体的定制内容,加速品牌传播,提升内容营销效果。

热门AI辅助写作AI工具讯飞绘文内容运营AI创作个性化文章多平台分发AI助手
材料星

材料星

专业的AI公文写作平台,公文写作神器

AI 材料星,专业的 AI 公文写作辅助平台,为体制内工作人员提供高效的公文写作解决方案。拥有海量公文文库、9 大核心 AI 功能,支持 30 + 文稿类型生成,助力快速完成领导讲话、工作总结、述职报告等材料,提升办公效率,是体制打工人的得力写作神器。

下拉加载更多