cd lama export TORCH_HOME=$(pwd) && export PYTHONPATH=$(pwd) 1. Download pre-trained models The best model (Places2, Places Challenge): curl -LJO https://huggingface.co/smartywu/big-lama/resolve/main/big-lama.zi
Image inpainting tool powered by SOTA AI Model django-rest-frameworktorchopencv-pythoninpaintinglamastable-diffusion UpdatedOct 29, 2022 Python Implementation of an Account Manager for LDAP in Django ldapdjangolama UpdatedNov 29, 2021 JavaScript
cd lama export TORCH_HOME=$(pwd) && export PYTHONPATH=. 1. Download pre-trained models Install tool for yandex disk link extraction: pip3 install wldhx.yadisk-direct The best model (Places2, Places Challenge): curl -L $(yadisk-direct https://disk.yandex.ru/d/ouP6l8VJ0HpMZg) -o ...
export TORCH_HOME=$(pwd) && export PYTHONPATH=. Then download models forperceptual loss: mkdir -p ade20k/ade20k-resnet50dilated-ppm_deepsup/ wget -P ade20k/ade20k-resnet50dilated-ppm_deepsup/ http://sceneparsing.csail.mit.edu/model/pytorch/ade20k-resnet50dilated-ppm_deepsup/encoder_epoc...
# pip3 install torch==2.1.2 torchvision==0.16.2 --index-url https://download.pytorch.org/whl/rocm5.6 pip3 install iopaint iopaint start --model=lama --device=cpu --port=8080 That's it, you can start using IOPaint by visiting http://localhost:8080 in your web browser. All models ...
('uint8') return cur_res def build_lama_model( config_p: str, ckpt_p: str, device="cuda" ): predict_config = OmegaConf.load(config_p) predict_config.model.path = ckpt_p device = torch.device(device) train_config_path = os.path.join( predict_config.model.path, 'config.yaml') ...
python3 main.py --device=cuda --port=8080 --model=ldm --ldm-steps=50--ldm-steps: The larger the value, the better the result, but it will be more time-consumingDiffusion model is MUCH MORE slower than GANs(1080x720 image takes 8s on 3090), but it's possible to get better ...
model = torch.jit.load(model_path, map_location="cpu") model = model.to(device) app.run(host="0.0.0.0", port=args.port, debug=False) if __name__ == "__main__": main() 4 changes: 4 additions & 0 deletions 4 requirements.txt Show comments Edit file Delete file This file ...
Lama Cleaner make it easy to use SOTA AI model in just two commands: #In order to use the GPU, install cuda version of pytorch first.#pip install torch==1.13.1+cu117 --extra-index-url https://download.pytorch.org/whl/cu117pip install lama-cleaner lama-cleaner --model=lama --device...
cd lama export TORCH_HOME=$(pwd) && export PYTHONPATH=$(pwd) 1. Download pre-trained models Install tool for yandex disk link extraction: pip3 install wldhx.yadisk-direct The best model (Places2, Places Challenge): curl -L $(yadisk-direct https://disk.yandex.ru/d/ouP6l8VJ0HpMZg)...