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import torch
import gradio as gr
from diffusers import StableDiffusionControlNetImg2ImgPipeline, ControlNetModel
from diffusers.utils import load_image
import qrcode
# Set device CPU karena tidak ada GPU
device = "cpu"
# Load ControlNet model
controlnet = ControlNetModel.from_pretrained(
"DionTimmer/controlnet_qrcode-control_v1p_sd15",
torch_dtype=torch.float32
)
# Load pipeline
pipe = StableDiffusionControlNetImg2ImgPipeline.from_pretrained(
"runwayml/stable-diffusion-v1-5",
controlnet=controlnet,
torch_dtype=torch.float32,
safety_checker=None
).to(device)
def generate_qr(prompt, url_text):
# 1. Buat QR dasar dari teks/URL
qr = qrcode.QRCode(
version=1,
error_correction=qrcode.constants.ERROR_CORRECT_H,
box_size=10,
border=4,
)
qr.add_data(url_text)
qr.make(fit=True)
qr_img = qr.make_image(fill_color="black", back_color="white").convert("RGB")
# 2. Ubah ke gaya artistik dengan ControlNet
image = pipe(
prompt,
image=qr_img,
num_inference_steps=20,
guidance_scale=7.5
).images[0]
return image
demo = gr.Interface(
fn=generate_qr,
inputs=[
gr.Textbox(label="Prompt / Deskripsi Gaya Gambar"),
gr.Textbox(label="Teks atau URL untuk QR"),
],
outputs=gr.Image(label="QR Code Artistik")
)
if __name__ == "__main__":
demo.launch()
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