SongwuJob/Omost_with_SR

A revision for Omost with Real_ESRGAN for better image quality

Omost_with_SR

Omost_with_SR is a project forked by Omost, enhanced with Real-ESRGAN to provide super-resolution capabilities for improved image quality. We extend our gratitude to the contributors of both projects.

• If highres_scale > 1, the model will adopt the super resolution function, the entire process is: text inputs -> llm -> Canvus outputs -> txt2img -> sr -> img2img -> image outputs

• If highres_scale = 1, the model disable super resolution, the entire process is equal to the origin Omost： text inputs -> llm -> Canvus outputs -> txt2img -> image outputs

In particular, we provide a simple inference code Omost_generate.py and OmostAutoPipeline class in Omost_api.py to quickly use and debug.

Get Started

you can use the below deployment (requires 8GB Nvidia VRAM):

git clone https://github.com/SongwuJob/Omost_with_SR.git
cd Omost_with_SR
conda create -n omost python=3.10
conda activate omost
pip install torch torchvision --index-url https://download.pytorch.org/whl/cu121
pip install -r requirements.txt
python gradio_app.py

(Note that quant LLM requires bitsandbytes - some 9XX or 10XX or 20XX GPUs may have trouble in running it. If that happens, just use our official huggingface space.)

• You need to make sure that bitsandbytes==0.43.1 or you may have a problem.

• if ModuleNotFoundError: No module named‘torchvision.transforms.functional_tensor’，please revise as torchvision.transforms._functional_tensor.