Flux Upscale Model

--- base_model: - black-forest-labs/FLUX.1-dev library_name: diffusers license: other license_name: flux-1-dev-non-commercial-license license_link: https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/LICENSE.md pipeline_tag: image-to-image inference: False tags: - ControlNet - super-resolution - upscaler --- # ⚡ Flux.1-dev: Upscaler ControlNet ⚡ This is [Flux.1-dev](https://huggingface.co/black-forest-labs/FLUX.1-dev) ControlNet for low resolution images developed by Jasper research team. <p align="center"> <img style="width:700px;" src="examples/showcase.jpg"> </p> # How to use This model can be used directly with the `diffusers` library ```python import torch from diffusers.utils import load_image from diffusers import FluxControlNetModel from diffusers.pipelines import FluxControlNetPipeline # Load pipeline controlnet = FluxControlNetModel.from_pretrained( "jasperai/Flux.1-dev-Controlnet-Upscaler", torch_dtype=torch.bfloat16 ) pipe = FluxControlNetPipeline.from_pretrained( "black-forest-labs/FLUX.1-dev", controlnet=controlnet, torch_dtype=torch.bfloat16 ) pipe.to("cuda") # Load a control image control_image = load_image( "https://huggingface.co/jasperai/Flux.1-dev-Controlnet-Upscaler/resolve/main/examples/input.jpg" ) w, h = control_image.size # Upscale x4 control_image = control_image.resize((w * 4, h * 4)) image = pipe( prompt="", control_image=control_image, controlnet_conditioning_scale=0.6, num_inference_steps=28, guidance_scale=3.5, height=control_image.size[1], width=control_image.size[0] ).images[0] image ``` <p align="center"> <img style="width:500px;" src="examples/output.jpg"> </p> # Training This model was trained with a synthetic complex data degradation scheme taking as input a *real-life* image and artificially degrading it by combining several degradations such as amongst other image noising (Gaussian, Poisson), image blurring and JPEG compression in a similar spirit as [1] [1] Wang, Xintao, et al. "Real-esrgan: Training real-world blind super-resolution with pure synthetic data." Proceedings of the IEEE/CVF international conference on computer vision. 2021. # Licence This model falls under the [Flux.1-dev model licence](https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/LICENSE.md).

Source context: 5 downloads · 2 likes · Pipeline image-to-image · Library diffusers · Repo Virtuos-rnd/flux_upscale_model