--- library_name: diffusers license: apache-2.0 language: - en pipeline_tag: image-to-image --- # Fake-QRcode ControlNet These are ControlNet checkpoints trained on runwayml/stable-diffusion-v1-5 to generate recognizable AIGC QRcode image. ## Model Details Details will be added soon... ## Use with diffusers See the snippet below for usage with diffusers: ```python import cv2 import numpy as np import torch import os, sys from diffusers import StableDiffusionControlNetPipeline, ControlNetModel, AutoencoderKL, EulerAncestralDiscreteScheduler from PIL import Image controlnet = ControlNetModel.from_pretrained("ghoskno/Fake-Qrcode") pipe = StableDiffusionControlNetPipeline.from_pretrained( "runwayml/stable-diffusion-v1-5", controlnet=controlnet, torch_dtype=torch.float16 ) pipe.scheduler = DDIMScheduler.from_config(pipe.scheduler.config) pipe.enable_model_cpu_offload() generator = torch.manual_seed(412052000) qrcode = cv2.imread('path_to_qrcode.png') qrcode = cv2.resize(255 - qrcode, (1024, 1024)) image = pipe( "Blooming chinese chrysanthemum, green leaves growing wantonly, flowers, Complex patterns on the border, Masterpiece Art, Beauty, 8K, Unreal Engine", Image.fromarray(qrcode), generator=generator, num_inference_steps=37, guidance_scale=7, controlnet_conditioning_scale=1.85 ).images[0] ``` ## Some examples **input qrcode image** **prompt**: Blooming chinese chrysanthemum, green leaves growing wantonly, flowers, Complex patterns on the border, Masterpiece Art, Beauty, 8K, Unreal Engine **prompt**: Plum blossoms in the snow, pink stamens, green leaves and branches growing wantonly, flowers, Complex patterns on the border, Masterpiece Art, Beauty, 8K, Unreal Engine ## Limitations and Bias - No strict control by input prompt - Sometimes generate confusion or generate unrecognizable QRcode images