import paddle
import os
import gradio as gr
from PIL import Image
import qrcode
from ppdiffusers import (
StableDiffusionPipeline,
DiffusionPipeline,
ControlNetModel,
DDIMScheduler,
DPMSolverMultistepScheduler,
)
from PIL import Image
qrcode_generator = qrcode.QRCode(
version=1,
error_correction=qrcode.ERROR_CORRECT_H,
box_size=10,
border=4,
)
controlnet = ControlNetModel.from_pretrained(
"DionTimmer/controlnet_qrcode-control_v1p_sd15", paddle_dtype=paddle.float16
)
pipe = DiffusionPipeline.from_pretrained(
"runwayml/stable-diffusion-v1-5",
controlnet=controlnet,
safety_checker=None,
paddle_dtype=paddle.float16,
custom_pipeline="junnyu/stable_diffusion_controlnet_img2img",
)
pipe.enable_xformers_memory_efficient_attention()
pipe.scheduler = DDIMScheduler.from_config(pipe.scheduler.config)
sd_pipe = StableDiffusionPipeline.from_pretrained(
"stabilityai/stable-diffusion-2-1",
paddle_dtype=paddle.float16,
safety_checker=None,
)
sd_pipe.scheduler = DPMSolverMultistepScheduler.from_config(sd_pipe.scheduler.config)
sd_pipe.enable_xformers_memory_efficient_attention()
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,
qrcode_image: Image.Image = 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 = paddle.Generator().manual_seed(seed) if seed != -1 else None
if init_image is None or init_image.size == (1, 1):
print("Generating random image from prompt using Stable Diffusion")
out = sd_pipe(
prompt=prompt,
negative_prompt=negative_prompt,
generator=generator,
num_inference_steps=25,
num_images_per_prompt=1,
)
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,
width=768,
height=768,
guidance_scale=float(guidance_scale),
controlnet_conditioning_scale=float(controlnet_conditioning_scale),
generator=generator,
strength=float(strength),
num_inference_steps=40,
)
return out.images[0]
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/QR-code-AI-art-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/spaces/huggingface-projects/QR-code-AI-art-generator",
"billboard amidst the bustling skyline of New York City, with iconic landmarks subtly featured in the background.",
"ugly, disfigured, low quality, blurry, nsfw",
13.37,
2.81,
0.68,
2313123,
"./examples/hack.png",
"./examples/hack.png",
],
[
"https://huggingface.co/spaces/huggingface-projects/QR-code-AI-art-generator",
"beautiful sunset in San Francisco with Golden Gate bridge in the background",
"ugly, disfigured, low quality, blurry, nsfw",
11.01,
2.61,
0.66,
1423585430,
"./examples/hack.png",
"./examples/hack.png",
],
[
"https://huggingface.co",
"A flying cat over a jungle",
"ugly, disfigured, low quality, blurry, nsfw",
13,
2.81,
0.66,
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(concurrency_count=1, max_size=20)
blocks.launch(server_name="0.0.0.0", server_port=8235)
