HunyuanVideo-I2V

HunyuanVideo-I2V

HunyuanVideo-I2V is an open-source AI framework developed by Tencent that transforms static images into high-quality, dynamic videos with customizable motion effects and exceptional visual consistency.
https://github.com/Tencent/HunyuanVideo-I2V?ref=producthunt
HunyuanVideo-I2V

Thông tin Sản phẩm

Đã cập nhật:Nov 25, 2025

HunyuanVideo-I2V là gì

HunyuanVideo-I2V is a cutting-edge image-to-video generation model based on the successful HunyuanVideo foundation. Released by Tencent's Hunyuan Lab, it represents a significant advancement in AI-powered video synthesis, capable of generating videos up to 720P resolution and 129 frames (5 seconds) in length. The framework is designed to bridge the gap between static imagery and dynamic video content, offering both stability and high-dynamic motion options to suit different creative needs. It comes with comprehensive tools for customization, including LoRA training capabilities for specialized video effects.

Các Tính năng Chính của HunyuanVideo-I2V

HunyuanVideo-I2V is an advanced open-source image-to-video generation framework developed by Tencent that transforms static images into high-quality dynamic videos. It leverages a pre-trained Multimodal Large Language Model with a Decoder-Only architecture, enabling comprehensive understanding of both image and text inputs. The framework supports high-resolution video generation up to 720P and video length up to 129 frames (5 seconds), with options for both stable and dynamic video generation modes.
Unified Image and Video Architecture: Employs a Transformer design with full attention mechanism that supports unified generation of both images and videos, enabling seamless integration of image and text information
Customizable Motion Control: Offers flexible control over video dynamics through stability settings and flow-shift parameters, allowing users to generate either stable or highly dynamic videos
High-Resolution Output: Capable of generating high-quality videos up to 720P resolution with 129 frames, maintaining visual consistency throughout the generation process
LoRA Training Support: Includes LoRA training capabilities for customizable special effects, allowing users to train and apply specific video effects to their generations

Các Trường hợp Sử dụng của HunyuanVideo-I2V

Digital Content Creation: Enables content creators to transform static promotional images into engaging video content for social media and advertising
Educational Animation: Converts educational diagrams and illustrations into animated videos for better understanding and engagement in learning materials
Special Effects Production: Allows filmmakers and video producers to create custom special effects through LoRA training for unique visual transitions and animations
Art Animation: Helps artists bring their static artwork to life through automated animation, creating dynamic versions of paintings or illustrations

Ưu điểm

Open-source availability with comprehensive documentation
High-quality output with resolution up to 720P
Flexible control over video dynamics and motion
Support for customizable effects through LoRA training

Nhược điểm

High hardware requirements (minimum 60GB GPU memory)
Limited to Linux operating system
Maximum video length restricted to 5 seconds (129 frames)

Cách Sử dụng HunyuanVideo-I2V

1. System Requirements Check: Ensure you have: 1) NVIDIA GPU with minimum 60GB memory (80GB recommended) for 720p video generation 2) Linux operating system 3) CUDA support
2. Install Dependencies: Run these commands in sequence: 1. git clone https://github.com/Tencent-Hunyuan/HunyuanVideo-I2V 2. cd HunyuanVideo-I2V 3. conda create -n HunyuanVideo-I2V python==3.11.9 4. conda activate HunyuanVideo-I2V 5. conda install pytorch==2.4.0 torchvision==0.19.0 torchaudio==2.4.0 pytorch-cuda=12.4 -c pytorch -c nvidia 6. python -m pip install -r requirements.txt 7. python -m pip install ninja 8. python -m pip install git+https://github.com/Dao-AILab/[email protected] 9. python -m pip install xfuser==0.4.0
3. Download Pre-trained Models: Follow the instructions in ckpts/README.md to download the required model weights
4. Generate Stable Video: Run command: python3 sample_image2video.py \ --model HYVideo-T/2 \ --prompt "[your prompt]" \ --i2v-mode \ --i2v-image-path [path to input image] \ --i2v-resolution 720p \ --i2v-stability \ --infer-steps 50 \ --video-length 129 \ --flow-reverse \ --flow-shift 7.0 \ --seed 0 \ --embedded-cfg-scale 6.0 \ --use-cpu-offload \ --save-path ./results
5. Generate Dynamic Video: Similar to step 4 but remove --i2v-stability flag and change --flow-shift to 17.0 for more dynamic motion
6. Optional: Multi-GPU Parallel Processing: For faster processing on multiple GPUs, use: ALLOW_RESIZE_FOR_SP=1 torchrun --nproc_per_node=8 \ sample_image2video.py [other parameters as in step 4] \ --ulysses-degree 8 \ --ring-degree 1
7. Tips for Best Results: 1. Use concise prompts 2. Include main subject, action, and optional background/camera angle 3. Avoid overly detailed prompts 4. Use --i2v-stability for stable videos 5. Adjust --flow-shift between 7.0 (stable) and 17.0 (dynamic) based on needs

Câu hỏi Thường gặp về HunyuanVideo-I2V

The minimum GPU memory required is 60GB for 720p video generation. A GPU with 80GB of memory is recommended for better generation quality. The model requires an NVIDIA GPU with CUDA support and has been tested on Linux operating system.

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