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This workflow is designed for speed and ease of use. It generates high-quality 2.5s videos in under 90 seconds (depending on GPU) using the Wan 2.2 5B model.
Laufzeitprofil
Quellenbeschreibung
This workflow is designed for speed and ease of use. It generates high-quality 2.5s videos in under 90 seconds (depending on GPU) using the Wan 2.2 5B model.
✨ Key Features:
KI-generierter Kommentar
KI-generierte Erklärung auf Grundlage von Quellen- und Konfigurationsdetails. Vorschläge sind klar gekennzeichnet.
This ComfyUI workflow animates an uploaded starting image with a motion prompt into a 2.5-second video, then saves the result in WebP and WebM formats.
WD14 Tagger analyzes the input image and generates tags.
The workflow combines the image tags with your manual prompt before generating the video.
Upload the starting image in the Load Image node and enter the motion description in the ttN text node.
The workflow outputs a 2.5-second clip in WebP and WebM formats.
In ComfyUI, use ComfyUI Manager to install missing custom nodes.
Vorschlag · nicht geprüft
The workflow needs these node packs: comfyui-custom-scripts, ComfyUI_JPS-Nodes, comfyui_tinyterranodes, and comfyui-wd14-tagger.
Prepare these model files: wan2.2_ti2v_5B_fp16.safetensors, wan2.2_vae.safetensors, and umt5_xxl_fp16.safetensors.
Enter the motion prompt in the ttN text node; examples include “smiling,” “wind blowing,” and “blinking.”
The workflow uses 10 generation steps.
This item is a workflow; a Pipe version is not available.
Before use, verify that wan2.2_ti2v_5B_fp16.safetensors is the intended model file and that the listed model files are available.
Vorschlag · nicht geprüft
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Quellen
1 QuelleQuellenauszüge
1 AuszugSource context: 628 downloads · Type Workflows · Base model Wan Video 2.2 TI2V-5B
Auto-Captioning: Uses WD14 Tagger to automatically analyze your input image and generate tags.
Smart Prompting: Automatically concatenates your manual prompt with the image tags to ensure the video stays true to the source image.
Fast Generation: Optimized for speed (10 steps) without sacrificing too much quality.
Dual Output: Saves in both WebP and WebM formats.
🛠️ How to use:
Load Image: Upload your starting image in the "Load Image" node.
Add Motion Prompt: In the "ttN text" node (green box), describe the movement you want (e.g., "smiling, wind blowing, blinking").
Run: The workflow will combine your text with the visual description of the image and generate the video.
📦 Requirements (ComfyUI):
Please use ComfyUI Manager* to "Install Missing Custom Nodes".
Required Models:
UNET: wan2.2_ti2v_5B_fp16.safetensors
VAE: wan2.2_vae.safetensors
CLIP: umt5_xxl_fp16.safetensors
💡 Performance:
Tested on mid-range GPUs. Generates a 2.5-second clip in approx 1:30 minutes.
Created to help you animate static images quickly! Enjoy.
Geschätzter VRAM Bedarf
Schätzung nicht verfügbar
11,9 GB über 2 von 3 Modell-Dateien. Gesamtmodell-Dateien + 25% Ladeaufwand + 2 GB Ausführungs-Puffer, aufgerundet.
Anforderungen
7 AnforderungenText encoder · 10.6 GB · SAFETENSORS · Unknown
VAE · 1.31 GB · SAFETENSORS · fp8 · pruned · Unknown
Knotenpaket · Registry
Knotenpaket · Registry
Knotenpaket · Registry
Knotenpaket · Registry
