With the rapid development of artificial intelligence technology, video generation has become a reality. Today, we are excited to introduce an open-source project called CogVideoX, developed by a team from Tsinghua University. This project takes the capability of converting text to video to a new height.
CogVideoX: A New Chapter in Video Generation
CogVideoX is a large text-to-video generation model based on Transformer technology. It was first open-sourced in May 2022 and received a significant update on August 6, 2024. The latest update includes the open-sourcing of 3D Causal VAE technology used for the CogVideoX 2B model, which almost losslessly reconstructs videos. Additionally, the first model in the CogVideoX series, CogVideoX 2B, has been open-sourced, bringing new vitality to the field of video generation.
Technical Details and Performance
The CogVideoX model supports English prompts and can generate videos that are 6 seconds long, with 8 frames per second, and a resolution of 720*480. Currently, using diffusers for inference consumes 36GB of memory, while using SAT consumes 18GB. Additionally, fine-tuning memory consumption is 42GB, and the maximum prompt length is 226 tokens.
Quick Start Guide
Open-source address: https://github.com/THUDM/CogVideo
The above AI tool has been packaged into a local one-click startup package. You only need to click to use it on your personal computer, eliminating concerns about privacy leaks and configuration issues.
Computer Configuration Requirements
Download and Usage Tutorial
Text-to-Video Prompt Tips
The accuracy and level of detail in the prompts directly affect the quality of the video content. Using structured prompts can greatly enhance the relevance and professionalism of the video content. Here are the key components for constructing prompts:
Prompt = (Camera Language + Shot Angle + Lighting) + Subject (Subject Description) + Subject Movement + Scene (Scene Description) + (Atmosphere)
Camera Language: Using various camera applications and transitions to convey stories or information and create specific visual effects and emotional atmospheres, such as panning, zooming in and out, elevating shots, tilting, tracking shots, handheld shots, drone shots, etc.
Shot Angle: Controlling the distance and angle between the camera and the subject to achieve different visual effects and emotional expressions, such as wide shots, medium shots, close-ups, bird's-eye view, follow shots, fisheye effects, etc.
Lighting: Lighting is a key element that gives soul to photographic works. The use of lighting can make photos more layered and emotional. We can create works with rich layers and emotional expressiveness through lighting, such as natural light, Tyndall effect, soft diffusion, hard direct light, backlit silhouettes, three-point lighting, etc.
Subject: The main object of expression in the video, such as children, lions, sunflowers, cars, castles, etc.
Subject Description: Describing the details of the subject's appearance and posture, such as the character's clothing, animal fur color, plant color, object state, and architectural style.
Subject Movement: Describing the subject's motion state, including static and dynamic states. The motion state should not be overly complex and should fit within the 6-second video duration.
Scene: The environment in which the subject is located, including foreground and background.
Scene Description: Describing the details of the environment where the subject is located, such as urban settings, rural landscapes, industrial areas, etc.
Atmosphere: Describing the atmosphere of the expected video screen, such as bustling and busy, suspenseful and thrilling, serene and comfortable, etc.
Other Tips
Keyword Repetition: Repeating or emphasizing keywords in different parts of the prompt can help improve output consistency, such as: "The camera quickly flies over the forest at super-fast speed."
Focus on Content: The prompt should focus on the content that should be in the video, such as: "a deserted street," rather than "a street with no people."
Excited? Give it a try! This open-source project from Tsinghua University is sure to amaze you!
