必须先从 Hugging Face 手动下载模型权重,否则无法运行;PyTorch 需装 cu128 版本,版本不匹配易出错;当前分辨率上限 1024x1024,插画与视频生成效果有限。
git clone https://github.com/FotographerAI/ZenCtrl.git
cd ZenCtrl
pip install torch==2.7.0+cu128 torchvision torchaudio --index-url https://download.pytorch.org/whl/cu128
pip install -r requirements.txt
curl --create-dirs -L https://huggingface.co/fotographerai/zenctrl_tools/resolve/main/weights/zen2con_1440_17000/pytorch_lora_weights.safetensors -o weights\zen2con_1440_17000\pytorch_lora_weights.safetensors
python app/gradio_app.pyREADME 未说明显存要求;安装命令使用 CUDA 12.8 版 PyTorch,需 NVIDIA GPU,具体型号未说明。
基于单张主体图做免微调的多视角可控图像生成框架,保持前景保真
在保持前景细节不变的前提下,用参考图驱动扩散模型生成新场景,适合需要主体一致性的图像编辑与合成。
核心能力
- 单张主体图即可生成,无需微调
- 控制形状、姿态、相机角度与场景上下文
- 基于 FLUX.1 的主体生成模型,输出 1024x1024
- 提供背景生成加 Canny 控制与去模糊模型
- Gradio 应用开箱即用,含预处理与编辑模块规划
容易踩的坑
暂无 release 数据(可能没有发版,或尚未同步)。
用户点评
登录用户的真实使用记录,可按版本和硬件筛选还没有人点评。第一个说出真实体验的人最有价值。
An all-in-one, control framework for unified visual content creation using GenAI.
Generate multi-view, diverse-scene, and task-specific high-resolution images from a single subject image—without fine-tuning.
🧠 Overview
ZenCtrl is a comprehensive toolkit built to tackle core challenges in image generation:
- No fine-tuning needed – works from a single subject image
- Maintains control over shape, pose, camera angle, context
- Supports high-resolution, multi-scene generation
- Modular toolkit for preprocessing, control, editing, and post-processing tasks
ZenCtrl is based on OminiControl but enhanced with more fine-grained control, consistent subject preservation, and more improved and ready-to-use models. Our goal is to build an agentic visual generation system that can orchestrate image/video creation from LLM-driven recipes.
🛠 Toolkit Components (coming soon)
🧹 Preprocessing
- Background removal
- Matting
- Reshaping
- Segmentation
🎮 Control Models
- Shape (HED, Scribble, Depth)
- Pose (OpenPose, DensePose)
- Mask control
- Camera/View control
🎨 Post-processing
- Deblurring
- Color fixing
- Natural blending
✏️ Editing Models
- Inpainting (removal, masked editing, replacement)
- Outpainting
- Transformation / Motion
- Relighting
🎯 Supported Tasks
- Background generation
- Controlled background generation
- Subject-consistent context-aware generation
- Object and subject placement (coming soon)
- In-context image/video generation (coming soon)
- Multi-object/subject merging & blending (coming soon)
- Video generation (coming soon)
📦 Target Use Cases
- Product photography
- Fashion & accessory try-on
- Virtual try-on (shoes, hats, glasses, etc.)
- People & portrait control
- Illustration, animation, and ad creatives
All of these tasks can be mixed and layered — ZenCtrl is designed to support real-world visual workflows with agentic task composition.
📢 News
- 2025-03-24: 🧠 First release — model weights available on Hugging Face!
- 2025-05-06: 📢 Update — ource code release, latest model weights available on Hugging Face!
- Coming Soon: Quick Start guide, Upscaling source code, Example notebooks
- Next: Controlled fine-grain version on our platform and API (Pro version)
- Future: Video generation toolkit release
🚀 Quick Start
Before running the Gradio code, please install the requirements and download the weights from our HuggingFace repository:
👉 https://huggingface.co/fotographerai/zenctrl_tools
We matched our original code with the Omnicontrol structure. Our model takes two inputs instead, but we are going to release the original code soon with the LLaMA task driver — so stay tuned. We will also update the tasks for specific verticals (e.g., virtual try-on, ad creatives, etc.).
Quick Setup (CMD)
You can follow the step-by-step setup instructions below:
*** Cloning and setting up ZenCtrl
git clone https://github.com/FotographerAI/ZenCtrl.git
cd ZenCtrl
*** Creating virtual environment
python -m venv venv
call venv\Scripts\activate.bat
*** Installing PyTorch and requirements
pip install torch==2.7.0+cu128 torchvision torchaudio --index-url https://download.pytorch.org/whl/cu128
pip install --upgrade pip wheel setuptools
pip install -r requirements.txt
*** Downloading model weights
curl --create-dirs -L https://huggingface.co/fotographerai/zenctrl_tools/resolve/main/weights/zen2con_1440_17000/pytorch_lora_weights.safetensors -o weights\zen2con_1440_17000\pytorch_lora_weights.safetensors
*** All set! Launching Gradio app
python app/gradio_app.py
🎨 Demo
Examples
🧪 Try it now on Hugging Face Space
🔧 Models (Updated Weights Released)
| Type | Name | Base | Resolution | Description | links |
|---|---|---|---|---|---|
| Subject Generation | zen2con_1440_17000 | FLUX.1 | 1024x1024 | Core model for subject-driven gen | link |
| Bg generation + Canny | bg_canny_58000_1024 | FLUX.1 | 1024x1024 | Enhanced background control | link |
| Deblurring Model | deblurr_1024_10000 | OminiControl | 1024x1024 | Quality recovery post-generation | link |
🚧 Limitations
- Models currently perform best with objects, and to some extent humans.
- Resolution support is currently capped at 1024x1024 (higher quality coming soon).
- Performance with illustrations is currently limited.
- The models were not trained on large-scale or highly diverse datasets yet — we plan to improve quality and variation by training on larger and more diverse datasets, especially for illustration and stylized content.
- Video support and the full agentic task pipeline are still under development.
📋 To-do
- Release early pretrained model weights for defined tasks
- Release additional task-specific models and modes
- Release open source code
- Launch API access via Baseten for easier deployment
- Release Quick Start guide and example notebooks
- Launch API access via our app for easier deployment
- Release high-resolution models (1500×1500+)
- Enable full toolkit integration with agent API
- Add video generation module
🤝 Join the Community
- 💬 Discord – share ideas and feedback
- 🌐 Landing Page
- 🧪 Try it now on Hugging Face Space
🤝 Community Collaboration
We hope to collaborate closely with the open-source community to make ZenCtrl a powerful and extensible toolkit for visual content creation.
Once the source code is released, we welcome contributions in training, expanding supported use cases, and developing new task-specific modules.
Our vision is to make ZenCtrl the standard framework for agentic, high-quality image and video generation — built together, for everyone.