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Wan2.2 Fun Control Video (GGUF) 4 Steps

7

178

2

Updated: Sep 10, 2025

base model

Type

Workflows

Stats

178

0

Reviews

Published

Sep 10, 2025

Base Model

Wan Video 2.2 I2V-A14B

Hash

AutoV2
5A3DB196AE
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zardozai

🎮 Wan2.2 14B Fun Control Video - GGUF Workflow with Canny Edge Detection

Take full control of your video generation with this advanced Wan2.2 workflow featuring real-time control video guidance!

✨ Key Features:

• Control Video Integration: Use any video as motion/structure guidance

• Canny Edge Processing: Automatic edge detection for precise control

• Reference Image Support: Maintain character/style consistency

• GGUF Optimized: Memory-efficient Q8_0 quantization

• Dual-Stage Pipeline: High/Low noise models for premium quality

• 4-Step LoRA Speed: Ultra-fast generation with distilled LoRAs

🔧 Technical Specs:

• Model: Wan2.2-Fun-A14B-Control (High/Low Noise)

• Quantization: Q8_0 GGUF format

• Control Method: Canny edge detection

• Resolution: 480x480 (customizable)

• Frames: 81 frames at 16fps

• Processing: Automatic video preprocessing

💡 Use Cases:

• Dance video recreation

• Motion transfer

• Character animation

• Structure-guided generation

• Style transfer with motion control

📋 Requirements:

• Control video (MP4)

• Reference image

• ComfyUI with ControlNet aux nodes

• GGUF models from QuantStack

Transform any video into your creative vision while maintaining perfect motion control!

#Wan22 #ControlNet #GGUF #ComfyUI #VideoControl #AI