sd-controlnet-canny/app.py

65 lines
2.1 KiB
Python

from diffusers import StableDiffusionControlNetPipeline, ControlNetModel, UniPCMultistepScheduler
import torch
from controlnet_aux import OpenposeDetector
from diffusers.utils import load_image
from gradio.themes.utils import sizes
import gradio as gr
import cv2
import numpy as np
from PIL import Image
theme = gr.themes.Default(radius_size=sizes.radius_none).set(
block_label_text_color = '#4D63FF',
block_title_text_color = '#4D63FF',
button_primary_text_color = '#4D63FF',
button_primary_background_fill='#FFFFFF',
button_primary_border_color='#4D63FF',
button_primary_background_fill_hover='#EDEFFF',
)
controlnet = ControlNetModel.from_pretrained(
"lllyasviel/sd-controlnet-canny", torch_dtype=torch.float16
)
pipe = StableDiffusionControlNetPipeline.from_pretrained(
"runwayml/stable-diffusion-v1-5", controlnet=controlnet, safety_checker=None, torch_dtype=torch.float16
)
pipe.scheduler = UniPCMultistepScheduler.from_config(pipe.scheduler.config)
pipe.enable_xformers_memory_efficient_attention()
pipe.enable_model_cpu_offload()
def image2image(image, prompt):
#image = np.array(image)
low_threshold = 100
high_threshold = 200
image = cv2.Canny(image, low_threshold, high_threshold)
image = image[:, :, None]
image = np.concatenate([image, image, image], axis=2)
image = Image.fromarray(image)
image = pipe(prompt, image, num_inference_steps=20).images[0]
return image
with gr.Blocks(theme=theme, css="footer {visibility: hidden}") as demo:
gr.Markdown("""
<div align='center' ><font size='60'>根据边缘生成图片</font></div>
""")
with gr.Row():
with gr.Column():
image = gr.Image(label="图片", type='numpy')
prompt = gr.Textbox(label="提示词")
with gr.Row():
button = gr.Button("提交", variant="primary")
box2 = gr.Image(label="图片")
button.click(fn=image2image, inputs=[image, prompt], outputs=box2)
examples = gr.Examples(examples=[['bird.png', 'bird']], inputs=[image, prompt], label="例子")
if __name__ == "__main__":
demo.queue(concurrency_count=3).launch(server_name = "0.0.0.0")