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    ControlNeXt


    🤖 Github | 📝 Project Page | 📚 Paper | 🗂️ Demo (SDXL)


    ControlNeXt is our official implementation for controllable generation, supporting both images and videos while incorporating diverse forms of control information. In this project, we propose a new method that reduces trainable parameters by up to 90% compared with ControlNet, achieving faster convergence and outstanding efficiency. This method can be directly combined with other LoRA techniques to alter style and ensure more stable generation. Please refer to the examples for more details.

    We provide an online demo of ControlNeXt-SDXL. Due to the high resource requirements of SVD, we are unable to offer it online.

    🎥 Examples


    demo1.jpgdemo3.jpgdemo5.jpg

    🛠️ Usage


    🚀 Quick Start


    Here, we use ControlNeXt-SDXL AnimeCanny as an example.

    First of all, you have to make sure that you have Python installed (since you play AI, this should be default for you).

    Launch your terminal and run the following command to clone our Github repository:

    git clone https://github.com/dvlab-research/ControlNeXt
    cd ControlNeXt/ControlNeXt-SDXL

    And install the required packages:

    pip install -r requirements.txt

    (Optional) Download the LoRA weight, such as Amiya (Arknights) Fresh Art Style. And put them under lora/ directory (or other directory you like).

    Finally, run our example:

    bash examples/anime_canny/run.sh

    If you download models by yourself, you may revise the bash script:

    # examples/anime_canny/run.sh
    python run_controlnext.py --pretrained_model_name_or_path "neta-art/neta-xl-2.0" \
      --unet_model_name_or_path "Eugeoter/controlnext-sdxl-anime-canny" \ # Huggingface repo id or local file path to your ControlNeXt UNet model.
      --controlnet_model_name_or_path "Eugeoter/controlnext-sdxl-anime-canny" \ # Huggingface repo id or local file path to your ControlNeXt ControlNet model.
      --controlnet_scale 1.0 \ # controlnet scale factor used to adjust the strength of the control condition
      --vae_model_name_or_path "madebyollin/sdxl-vae-fp16-fix" \
      --validation_prompt "3d style, photorealistic style, 1girl, arknights, amiya (arknights), solo, white background, upper body, looking at viewer, blush, closed mouth, low ponytail, black jacket, hooded jacket, open jacket, hood down, blue neckwear" \
      --negative_prompt "worst quality, abstract, clumsy pose, deformed hand, fused fingers, extra digits, fewer digits, fewer fingers, extra fingers, extra arm, missing arm, extra leg, missing leg, signature, artist name, multi views, disfigured, ugly" \
      --validation_image "examples/anime_canny/condition_0.png" \ # input canny image
      --output_dir "examples/anime_canny" \
      --load_weight_increasement # load weight increasement

    📝 More


    For more usages and examples, please refer to our Github project page.

    Description

    FAQ

    Comments (3)

    niniconconSep 6, 2024
    CivitAI

    Can you explain the installation better? not understanding how to get this working or where to put the files

    Euge_
    Author
    Sep 6, 2024

    Sure. Actually, this is our research project and you have to run with our code rather than any webui/comfyui. This requires some basic coding skill.

    If you're willing to try. You do not need to download the model weights from here (civitai). For a quick start, all you need to do is running the four-line command in the model introduction.

    Thanks for your like!

    duemellon142Sep 26, 2024
    CivitAI

    I just don't understand what these do or how they compare. I followed the page & it focused on the Canny, not the VitDepth or the Fashion.

    Other
    SD 1.5

    Details

    Downloads
    36
    Platform
    CivitAI
    Platform Status
    Available
    Created
    9/5/2024
    Updated
    8/28/2026
    Deleted
    -

    Files

    controlnext_sd15Deepfashion.zip

    Mirrors