app.py

import torch
import gradio as gr
from PIL import Image
import qrcode
from pathlib import Path

from diffusers import (
 StableDiffusionPipeline,
 StableDiffusionControlNetImg2ImgPipeline,
 ControlNetModel,
 DDIMScheduler,
 DPMSolverMultistepScheduler,
)

from PIL import Image

qrcode_generator = qrcode.QRCode(
 version=1,
 error_correction=qrcode.constants.ERROR_CORRECT_H,
 box_size=10,
 border=0,
)

controlnet = ControlNetModel.from_pretrained(
 "DionTimmer/controlnet_qrcode-control_v1p_sd15", torch_dtype=torch.float16
)

pipe = StableDiffusionControlNetImg2ImgPipeline.from_pretrained(
 "runwayml/stable-diffusion-v1-5",
 controlnet=controlnet,
 safety_checker=None,
 torch_dtype=torch.float16,
)

pipe.enable_xformers_memory_efficient_attention()
pipe.scheduler = DDIMScheduler.from_config(pipe.scheduler.config)
pipe.enable_model_cpu_offload()


sd_pipe = StableDiffusionPipeline.from_pretrained(
 "stabilityai/stable-diffusion-2-1", torch_dtype=torch.float16
)
sd_pipe.scheduler = DPMSolverMultistepScheduler.from_config(sd_pipe.scheduler.config)
sd_pipe = sd_pipe.to("cuda")


sd_pipe.enable_xformers_memory_efficient_attention()
sd_pipe.enable_model_cpu_offload()


def resize_for_condition_image(input_image: Image.Image, resolution: int):
 input_image = input_image.convert("RGB")
 W, H = input_image.size
 k = float(resolution) / min(H, W)
 H *= k
 W *= k
 H = int(round(H / 64.0)) * 64
 W = int(round(W / 64.0)) * 64
 img = input_image.resize((W, H), resample=Image.LANCZOS)
 return img


def inference(
 qr_code_content: str,
 prompt: str,
 negative_prompt: str,
 guidance_scale: float = 10.0,
 controlnet_conditioning_scale: float = 2.0,
 strength: float = 0.8,
 seed: int = -1,
 init_image: Image.Image | None = None,
 qrcode_image: Image.Image | None = None,
):
 if prompt is None or prompt == "":
 raise gr.Error("Prompt is required")

 if qrcode_image is None and qr_code_content == "":
 raise gr.Error("QR Code Image or QR Code Content is required")

 generator = torch.manual_seed(seed) if seed != -1 else torch.Generator()

 # hack due to gradio examples
 if init_image is None or init_image.size == (1, 1):
 print("Generating random image from prompt using Stable Diffusion")
 # generate image from prompt
 out = sd_pipe(
 prompt=prompt,
 negative_prompt=negative_prompt,
 generator=generator,
 num_inference_steps=25,
 num_images_per_prompt=1,
 ) # type: ignore

 init_image = out.images[0]
 else:
 print("Using provided init image")
 init_image = resize_for_condition_image(init_image, 768)

 if qr_code_content != "" or qrcode_image.size == (1, 1):
 print("Generating QR Code from content")
 qr = qrcode.QRCode(
 version=1,
 error_correction=qrcode.constants.ERROR_CORRECT_H,
 box_size=10,
 border=4,
 )
 qr.add_data(qr_code_content)
 qr.make(fit=True)

 qrcode_image = qr.make_image(fill_color="black", back_color="white")
 qrcode_image = resize_for_condition_image(qrcode_image, 768)
 else:
 print("Using QR Code Image")
 qrcode_image = resize_for_condition_image(qrcode_image, 768)

 out = pipe(
 prompt=prompt,
 negative_prompt=negative_prompt,
 image=init_image,
 control_image=qrcode_image, # type: ignore
 width=768, # type: ignore
 height=768, # type: ignore
 guidance_scale=float(guidance_scale),
 controlnet_conditioning_scale=float(controlnet_conditioning_scale), # type: ignore
 generator=generator,
 strength=float(strength),
 num_inference_steps=40,
 )
 return out.images[0] # type: ignore


with gr.Blocks() as blocks:
 gr.Markdown(
 """
# QR Code AI Art Generator

model: https://huggingface.co/DionTimmer/controlnet_qrcode-control_v1p_sd15

<a href="https://huggingface.co/spaces/huggingface-projects/AI-QR-code-generator?duplicate=true" style="display: inline-block;margin-top: .5em;margin-right: .25em;" target="_blank">
<img style="margin-bottom: 0em;display: inline;margin-top: -.25em;" src="https://bit.ly/3gLdBN6" alt="Duplicate Space"></a> for no queue on your own hardware.</p>
 """
 )

 with gr.Row():
 with gr.Column():
 qr_code_content = gr.Textbox(
 label="QR Code Content",
 info="QR Code Content or URL",
 value="",
 )
 prompt = gr.Textbox(
 label="Prompt",
 info="Prompt is required. If init image is not provided, then it will be generated from prompt using Stable Diffusion 2.1",
 )
 negative_prompt = gr.Textbox(
 label="Negative Prompt",
 value="ugly, disfigured, low quality, blurry, nsfw",
 )
 with gr.Accordion(label="Init Images (Optional)", open=False):
 init_image = gr.Image(label="Init Image (Optional)", type="pil")

 qr_code_image = gr.Image(
 label="QR Code Image (Optional)",
 type="pil",
 )

 with gr.Accordion(
 label="Params: The generated QR Code functionality is largely influenced by the parameters detailed below",
 open=False,
 ):
 guidance_scale = gr.Slider(
 minimum=0.0,
 maximum=50.0,
 step=0.01,
 value=10.0,
 label="Guidance Scale",
 )
 controlnet_conditioning_scale = gr.Slider(
 minimum=0.0,
 maximum=5.0,
 step=0.01,
 value=2.0,
 label="Controlnet Conditioning Scale",
 )
 strength = gr.Slider(
 minimum=0.0, maximum=1.0, step=0.01, value=0.8, label="Strength"
 )
 seed = gr.Slider(
 minimum=-1,
 maximum=9999999999,
 step=1,
 value=2313123,
 label="Seed",
 randomize=True,
 )
 with gr.Row():
 run_btn = gr.Button("Run")
 with gr.Column():
 result_image = gr.Image(label="Result Image")
 run_btn.click(
 inference,
 inputs=[
 qr_code_content,
 prompt,
 negative_prompt,
 guidance_scale,
 controlnet_conditioning_scale,
 strength,
 seed,
 init_image,
 qr_code_image,
 ],
 outputs=[result_image],
 )

 gr.Examples(
 examples=[
 [
 "https://huggingface.co",
 "crisp QR code prominently displayed on a billboard amidst the bustling skyline of New York City, with iconic landmarks subtly featured in the background.",
 "ugly, disfigured, low quality, blurry, nsfw",
 10.0,
 2.0,
 0.8,
 2313123,
 "./examples/init.jpeg",
 "./examples/hack.png",
 ],
 [
 "https://huggingface.co/spaces/huggingface-projects/AI-QR-code-generator",
 "beautiful sunset in San Francisco with Golden Gate bridge in the background",
 "ugly, disfigured, low quality, blurry, nsfw",
 14.7,
 2.7,
 0.75,
 1423585430,
 "./examples/hack.png",
 "./examples/hack.png",
 ],
 [
 "https://huggingface.co",
 "A flying cat over a jungle",
 "ugly, disfigured, low quality, blurry, nsfw",
 10.0,
 2.7,
 0.8,
 2702246671,
 "./examples/hack.png",
 "./examples/hack.png",
 ],
 [
 "",
 "crisp QR code prominently displayed on a billboard amidst the bustling skyline of New York City, with iconic landmarks subtly featured in the background.",
 "ugly, disfigured, low quality, blurry, nsfw",
 10.0,
 2.0,
 0.8,
 2313123,
 "./examples/init.jpeg",
 "./examples/qrcode.png",
 ],
 ],
 fn=inference,
 inputs=[
 qr_code_content,
 prompt,
 negative_prompt,
 guidance_scale,
 controlnet_conditioning_scale,
 strength,
 seed,
 init_image,
 qr_code_image,
 ],
 outputs=[result_image],
 cache_examples=True,
 )

blocks.queue()
blocks.launch()