Model reference · open weights
flux_dev_openpose_controlnet is an open-weight image model from raulc0399. AxForge deploys and operates it for you on dedicated EU-owned hardware — with the licence handled where one is required.
Available as managed deployment — configured and operated for you on dedicated EU hardware, quoted per deployment.
What it is
| Released by | raulc0399 |
|---|---|
| Type | Image models |
| Task | Text→image |
| Parameters (lead) | 744M |
| Runs with | diffusers |
| Released | 2024-09-26 |
| Popularity | 1k downloads / month |
| Licence | Commercial licence needed |
About
(big thanks to oxen.ai for sponsoring the GPU for the training)
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)
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
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:
Weights fall under the FLUX.1 [dev] Non-Commercial License
From the published model card. Full card on the HuggingFace links in the sidebar.
How it works
Using it via the API
Once AxForge deploys flux-dev-openpose-controlnet for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (flux-dev-openpose-controlnet below is illustrative; you get the exact model name on deployment.)
$ curl -sS https://api.axforge.ai/v1/images/generations \
-H "Authorization: Bearer $AXFORGE_API_KEY" \
-H "Content-Type: application/json" \
-d '{"model":"flux-dev-openpose-controlnet","prompt":"a red bicycle","size":"1024x1024"}'
Create an account — your API key is available in the console. 3M free tokens every 30 days with every new account.