--- license: other license_name: stabilityai-ai-community license_link: LICENSE.md language: - en base_model: - stabilityai/stable-diffusion-3.5-medium pipeline_tag: text-to-image ---
**Bokeh_Line_Control**
## Description - Input Image: Black and white line art or images processed with edge detection algorithms - Output Image: Generated images incorporating edge information This enables better control over the main subject features and composition, resulting in more vivid and realistic images. ## Example | input | output | Prompt | |---|---|---| | ![input](./images/001_line.png) | ![output](./images/001.png) | A cat looks up, close-up, sapphire eyes | | ![input](./images/002_line.png) | ![output](./images/002.png) | heron bird standing, closeup, graceful | | ![input](./images/003_line.png) | ![output](./images/003.png) | a modern build design | | ![input](./images/004_line.png) | ![output](./images/004.png) | A old woman talking | ## Use We recommend using ComfyUI for local inference ![input](./comfy.png) # With Bokeh ```python import torch from diffusers import StableDiffusion3ControlNetPipeline from diffusers import SD3ControlNetModel from diffusers.utils import load_image controlnet = SD3ControlNetModel.from_pretrained("tensorart/Bokeh_Depth_Control") pipe = StableDiffusion3ControlNetPipeline.from_pretrained( "tensorart/bokeh_3.5_medium", controlnet=controlnet ) pipe.to("cuda", torch.float16) control_image = load_image("https://huggingface.co/tensorart/Bokeh_Line_Control/resolve/main/images/001_line.png") prompt = "A cat looks up, close-up, sapphire eyes" negative_prompt ="anime,render,cartoon,3d" negative_prompt_3="" image = pipe( prompt, num_inference_steps=30, negative_prompt=negative_prompt, control_image=control_image, height=1728, width=1152, guidance_scale=4, controlnet_conditioning_scale=0.8 ).images[0] image.save('image.jpg') ``` ## Contact * Website: https://tensor.art https://tusiart.com * Developed by: TensorArt * Api: https://tams.tensor.art/