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--- |
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library_name: diffusers |
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license: apache-2.0 |
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language: |
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- en |
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pipeline_tag: image-to-image |
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--- |
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# Fake-QRcode ControlNet |
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These are ControlNet checkpoints trained on runwayml/stable-diffusion-v1-5 to generate recognizable AIGC QRcode image. |
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## Model Details |
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Details will be added soon... |
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## Use with diffusers |
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See the snippet below for usage with diffusers: |
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```python |
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import cv2 |
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import numpy as np |
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import torch |
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import os, sys |
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from diffusers import StableDiffusionControlNetPipeline, ControlNetModel, AutoencoderKL, EulerAncestralDiscreteScheduler |
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from PIL import Image |
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controlnet = ControlNetModel.from_pretrained("ghoskno/Fake-Qrcode") |
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pipe = StableDiffusionControlNetPipeline.from_pretrained( |
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"runwayml/stable-diffusion-v1-5", controlnet=controlnet, torch_dtype=torch.float16 |
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) |
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pipe.scheduler = DDIMScheduler.from_config(pipe.scheduler.config) |
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pipe.enable_model_cpu_offload() |
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generator = torch.manual_seed(412052000) |
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qrcode = cv2.imread('path_to_qrcode.png') |
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qrcode = cv2.resize(255 - qrcode, (1024, 1024)) |
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image = pipe( |
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"Blooming chinese chrysanthemum, green leaves growing wantonly, flowers, Complex patterns on the border, Masterpiece Art, Beauty, 8K, Unreal Engine", |
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Image.fromarray(qrcode), |
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generator=generator, |
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num_inference_steps=37, |
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guidance_scale=7, |
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controlnet_conditioning_scale=1.85 |
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).images[0] |
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``` |
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## Some examples |
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**input qrcode image** |
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<img src="./ghoskno.png" style="zoom: 33%;" /> |
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**prompt**: Blooming chinese chrysanthemum, green leaves growing wantonly, flowers, Complex patterns on the border, Masterpiece Art, Beauty, 8K, Unreal Engine |
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<img src="./1.jpg" style="zoom: 33%;" /> |
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**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 |
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<img src="./2.jpg" style="zoom: 33%;" /> |
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## Limitations and Bias |
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- No strict control by input prompt |
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- Sometimes generate confusion or generate unrecognizable QRcode images |
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