Instructions to use raulc0399/flux_dev_openpose_controlnet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use raulc0399/flux_dev_openpose_controlnet with Diffusers:
pip install -U diffusers transformers accelerate
from diffusers import ControlNetModel, StableDiffusionControlNetPipeline controlnet = ControlNetModel.from_pretrained("raulc0399/flux_dev_openpose_controlnet") pipe = StableDiffusionControlNetPipeline.from_pretrained( "fill-in-base-model", controlnet=controlnet ) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
| license: other | |
| license_name: flux-1-dev-non-commercial-license | |
| license_link: https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/LICENSE. | |
| datasets: | |
| - raulc0399/open_pose_controlnet | |
| language: | |
| - en | |
| pipeline_tag: text-to-image | |
| tags: | |
| - Stable Diffusion | |
| - image-generation | |
| - Flux | |
| - diffusers | |
| - controlnet | |
| # openpose controlnet for flux.dev | |
| (big thanks to [oxen.ai](https://www.oxen.ai/) for sponsoring the GPU for the training) | |
| ## inference | |
| an openpose controlnet for flux-dev, trained on https://huggingface.co/datasets/raulc0399/open_pose_controlnet | |
| the controlnet model is trained for the xlabs ai pipeline https://github.com/XLabs-AI/x-flux | |
| to install the pipeline, execute the following: | |
| ``` | |
| git clone https://github.com/XLabs-AI/x-flux.git | |
| cd x-flux | |
| python3 -m venv xflux_env | |
| source xflux_env/bin/activate | |
| pip install -r requirements.txt | |
| ``` | |
| to run the pipeline with controlnet: | |
| ``` | |
| python3 main.py \ | |
| --prompt "person enjoying a day at the park, full hd, cinematic" \ | |
| --image ~/open_pose_controlnet_dataset/validation_images/pose/3_pose_1024.jpg --control_type openpose \ | |
| --local_path ./model.safetensors \ | |
| --use_controlnet --model_type flux-dev \ | |
| --width 1024 --height 1024 --timestep_to_start_cfg 2 \ | |
| --num_steps 50 --true_gs 4 --guidance 4 \ | |
| --save_path ~/gen_imgs | |
| ``` | |
| if the image has already been preprocessed comment out the line #146 from src/flux/xflux_pipeline.py | |
| ``` | |
| # self.annotator = Annotator(control_type, self.other_device) | |
| ``` | |
| ## training | |
| ``` | |
| oxen clone https://hub.oxen.ai/raulc/open_pose_controlnet_dataset | |
| git clone https://github.com/raulc0399/x-flux.git | |
| cd x-flux | |
| git checkout open_pose_training | |
| python3 -m venv xflux_env | |
| source xflux_env/bin/activate | |
| pip install -r requirements.txt | |
| huggingface-cli login | |
| accelerate config | |
| mkdir images | |
| rsync -r ~/open_pose_controlnet_dataset/train/images/ images/ | |
| cp train_configs/test_openpose_controlnet.yaml train_configs/openpose_controlnet.yaml | |
| accelerate launch train_flux_deepspeed_controlnet.py --config "train_configs/openpose_controlnet.yaml" | |
| ``` | |
| note 1: check the file train_configs/openpose_controlnet.yaml before starting | |
| note 2: rsync is needed, cp does not work with that many files | |
| note 3: the oxen repo has the caption files as json as expected by the training script | |
| ## results | |
| using these 2 images: | |
|  | |
|  | |
| with these prompts: | |
| "two friends sitting by each other enjoying a day at the park, full hd, cinematic" | |
| "person enjoying a day at the park, full hd, cinematic" | |
| resulted in these images: | |
|  | |
|  | |
| ## License | |
| Weights fall under the [FLUX.1 [dev]](https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/LICENSE.md) Non-Commercial License<br/> | |