Top 12 Open Source AI Video Generating Software For Linux

AI video generation has become the new norm for content creation, with hundreds of new software solutions available for Windows and Mac OS. However, if you are a Linux user, it might be a challenge for you to find suitable AI software to do this task. In this article, you'll explore 12 open source and free AI video generating software for Linux, along with features, so you can make the right choice.

Part 1. Top 12 AI Video Generating Software for Linux: Open Source and Free Tools

Open source software gives you free access to read, modify, and distribute its source code. Today, many free and open source video generation projects have been developed for Linux that let you create HD-quality videos within minutes. Here are the top 12 software you must explore.

1. StoryTeller

StoryTeller is the first AI video generating software for Linux on the list because of its ability to create exceptional animated videos. To create a video with StoryTeller, you just need to type a simple prompt, and it will generate the video for you with the help of three AI models.

In StoryTeller, ChatGPT completes your script, Stable Diffusion creates visuals for each sentence, and lastly, the neural text-to-speech model generates speech for your video.

Key Features:

• Its availability on PyPI makes it easy for you to install this software on your Linux OS.
• StoryTeller automatically saves the video file in a /out folder as /out.mp4.
• In the /out folder, you also get your video's audio file, subtitles, and image files as well.
• You can import the StoryTeller library into your Python code to use it in your projects.
• It lets you configure the model with small tweaks in the Python code to get customizable results.

2. Text2Video

Text2Video is a free AI Video generation software developed to improve the learning experience of students who want to learn by watching videos instead of reading dry academic text.

Interestingly, a college student developed this software using different coding languages, frameworks, APIs, and tools for his own use, which then got recognized by other fellows as well. To use this software on your Linux OS, you should have Node.js installed.

Key Features:

• Text2Video works as a web application that takes your reading material as input and turns it into a visually rich video for better learning.
• Important technologies used to develop this project are HTML, JavaScript, Node.js, CSS, ffmpegserver.js, CCapture.js, Amazon Polly, etc.
• It uses the Python web framework Flask and open source libraries like spaCy and gevent. The Pixabay API lets this software tool collect relevant royalty-free images and videos from the Pixabay website.
• Text2Video needs the CORS Anywhere proxy to avoid cross-origin resource sharing problems and let the different APIs work smoothly.

3. Wan2.2

Wan2.2 is a free, open-source video generation model made with intelligent technology for better video generation quality on your Linux OS. It cuts the computational cost with the use of the smart Mixture-of-Expert technique, and being trained on high-quality data, it gives you complete control over the aesthetics and style of your video.

Key Features:

• Wan 2.2 gives you the option to generate image-to-video and text-to-video. On top of that, you can also create text-image-to-video with your reference image and customized prompt, all in one framework.
• It's a 5 million-parameter hybrid TI2V model that generates videos with 720p resolution and 24fps that runs smoothly even on consumer-grade GPUs like the RTX 4090.
• The VAE architecture smartly compresses the videos up to 64x without compromising the quality of your video.
• 2 is trained on 83.2% more videos and 65.5% more images than the previous Wan2.1 model for improved video generation and aesthetics.

4. MoneyPrinterTurbo

MoneyPrinterTurbo is one of the simplest yet efficient AI video generation software tools for Linux that creates high-definition short videos without any complex input demands.

You just need to type in the video topic or a keyword, and the software will generate the whole video for you with a complete script, subtitles, and background audio.

Key Features:

• MoneyPrinterTurbo has a user-friendly interface and generates high-quality videos withaesthetic images, subtitles, and royalty-free audio. You can also use your own audio file and change the color, size, and font of the subtitles as well.
• It uses different APIs to fetch free video material and background audio for your videos.
• Supports multiple languages and lets you choose from different AI models like Moonshot, Azure, etc to generate your short videos.
• You can generate videos with both the horizontal 16:9 and vertical 9:16 aspect ratios using it.

5. Open-Sora

Open-Sora is a popular community-based AI video generation model that is developed to make high-quality video production accessible to everyone on Linux. Being open source, Open-Sora gives you the freedom to modify it and add improved features to the model.

Key Features:

• Open-Sora is developed on advanced deep learning techniques and can generate 15-second videos with up to 720p resolution in different video aspect ratios.
• The simple UI is easy enough for you to generate short videos with text, reference images, and even videos.
• Open-Sora features are optimized and updated on a regular basis, which makes it possible for you to try the best technology on time.
• All the training data and preparation codes are publicly available, so you can use them to customize the model according to your own needs.

6. Make-A-Video - Pytorch (wip)

Make-A-Video - Pytorch is Meta AI's text-to-video generation model developed using PyTorch.

It combines two important techniques, "pseudo-3D convolutions" and "Temporal attention," to give much better temporal fusion results. To create this model, the developers modified the text-to-image model "DALL-E2".

Key Features:

• Make-A-Video - Pytorch lets you generate high-quality videos with the use of textual descriptions.
• To train the model spatially when fed with 3D features, you can adjust the two modules accordingly.
• Modifications are made to the DALL-E2 model to improve attention across time, computational cost, and frame bridging for video generation.
• When images are passed during model training, both 3D convolutions and temporal attention are automatically skipped due to the nature of the images.

7. HunyuanVideo-I2V

HunyuanVideo-12V is developed on the foundational capabilities of the HunyuanVideo model that uses PyTorch to generate high-end videos for you using still reference pictures..

Key Features:

• Its customizable training options and the publicly available inference code and pre-trained model weights help you to deploy it easily on your Linux OS.
• The LoRA training code in the system lets you generate videos with special effects and high visual fidelity.
• It has FP8 quantized weights that reduce the memory space needed to store the model's original parameters and help it run smoothly.
• You can see the built-in demo videos to learn more about the functionalities of HunyuanVideo-I2V.
• You can also integrate HunyuanVideo-I2V with Hugging Face's Diffusers library to generate high-quality videos easily.
• Its code is checked and fixed for bugs periodically, and the regular updates let you use the latest features without any delay.

8. Video Diffusion - Pytorch

Stable diffusion is an image-to-video and text-to-video generating software that uses PyTorch. It uses a special space-time factored U-net architecture to design a 3D video for you from a 2D reference image.

Key Features:

• It's an open-source, free AI video generating software that uses the Denoising Diffusion Probabilistic Models to generate high-quality videos.
• For conditioning on text, it uses 2 versions of a language model, i.e., "BERT-large" and "BERT-base".
• With BERT-base, you can directly pass the video description as strings.
• Video diffusion saves the sample files (as GIF files) to a ./results folder at regular intervals.
• Also, the repository has trainer classes for training the model on a folder of gif files; it's important for all the gif files to be of the same dimension num_frames and image_size.

9. Phenaki - Pytorch

Phenaki - Pytorch is a different type of AI video generation model that uses MaskGIT and token critics to generate videos from text prompts using PyTorch. You can use this model to generate 2-minute-long videos from a text prompt in your Linux OS.

Key Features:

• Phenkai uses MaskGIT, which refines the video step by step in an iterative process.
• The token critics analyze each refined video frame and decide what part of the video needs further improvement, which is then again refined by MaskGIT.
• It's a free, open-source video generating software for Linux, so you can make changes to its source code and distribute it as well.

10. Wan2.1

Wan2.1 is a large-scale video generation model developed by the Wan team that takes your reference image or textual description to create high-resolution videos in Linux OS. This model is created on a diffusion-based architecture that lets you generate temporally consistent videos with high visual fidelity.

Key Features:

• 1 generates videos with flexible resolutions suitable for the different GPU hardware configurations.
• It is trained on large-scale, diverse video datasets to handle almost any scenario given to it and generate a video.
• Currently, it has 14 billion parameters and can generate videos for you with the same aesthetics and details as explained in the prompt or reference image.

11. VideoCrafter2

VideoCrafter2 is an upgraded AI video generation and editing toolbox for Linux that uses advanced diffusion models to generate cinematic videos from textual prompts and reference images. It can generate videos for you with improved character movement and creative concept combinations without the need to be trained on huge amounts of data.

Key Features:

• VideoVrafter2 has a special image-to-video model known as the DynamicCrafter that you can use to generate videos with high resolution and improved video coherence.
• The best part about VideoCrafter2 is that it produces high-quality videos even though it was trained on high-quality images and low-quality videos.
• You can also create videos with different artistic styles and real-world scenarios in it.
• There is a dedicated community on Discord for VideoCrafter2 where you can find help related to its installation and development on your Linux OS.

12. DCVGAN

DCVGAN: Depth Conditional Video Generation model uses an advanced Generative Adversarial Networks technique to train its model for both scene dynamics and visuals. With this model, you can generate hyper-realistic videos with advanced 3D scene dynamics and colors.

Key Features:

• Unlike normal generative adversarial networks, DCVGAN trains its model on depth videos and color videos to make sure your videos have both realistic scenes with colours and textures.
• DCGVAN uses facial expressions and hand gestures datasets to train its model with the help of generators and discriminators.
• First, depth videos are generated that are checked by the corresponding discriminator, and then colors are added to the depth videos to create color videos that are cross-checked by their discriminator to ensure realistic results in the video.
• You need to install Python version 3.7 along with PyTorch, OpenCV, FFmpeg, and Graphviz to use this model on your Linux OS.

Part 2. Make Videos from Text and Images In Linux Using HitPaw AI Video Generator

If you are a nomad user and not that tech-savvy, it can be difficult for you to use AI video generating software for Linux. Although these tools are free and open source projects, you need to download them manually; they often run into glitches, and most of the time, the generated videos are not that great.

Luckily for you, you can install Chrome on your Linux machine and then use HitPaw AI Video Generator to create awe-inspiring short clips from text prompts and reference images. The online nature of the tool gives you a direct way to do this from a browser.

Here are the steps:

• Step 1.Go to the official HitPaw Online AI Video Generator website. On the main page, choose either the "Text to Video" or the "Image to Video" option to begin. This opens up the workspace to generate AI videos.

  

• Step 2.Inside the Text to Video editor, choose an AI model of your choice. Then, type the prompt in detail to describe the concept of the video.

  

• Step 3.In the Image to Video dashboard, upload an image after you choose an AI model, and toggle on End Frame if you want to use two images to generate a video. Then again, type the prompt. HitPaw AI Video Generator also provides you with a ton of AI effects. Once you choose one, simply upload the image to apply the effect without needing a text prompt.

  

• Step 4.Next up, select the resolution (360p, 540p, 720p, or 1080p), choose the video duration (5 or 8 seconds), and opt for an aspect ratio for the intended display.

  

• Step 5.In both Text to Video and Image to Video, you can toggle on Auto Sound to add a background track. There is a negative prompt box as well to exclude whatever you don't want to see in the generated video.

  

• Step 6.Finally, click Generate to let the tool process your input, and once the video is ready in the right pane, click Download to save.

  

Part 3. FAQs of AI Video Generating Software for Linux

Conclusion on AI Video Generating Software for Linux

In this article, you have learned about the top open source and free AI video generating software for Linux. Each of them has specific features that make them unique from others and create high-quality videos with advanced technologies.

However, if you want to keep your hands away from technical stuff, then HitPaw AI Video Generator is the best alternative for you. It provides a clean, online, and user-friendly interface that lets you generate images using text or images without the hassle of installing new software.