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修复img2img的报错 (#4)
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import gradio as gr
from PIL import Image
import torch
from diffusers import (
StableDiffusionPipeline,
StableDiffusionImg2ImgPipeline,
StableDiffusionInpaintPipeline,
)
device="cuda"
model_id = "IDEA-CCNL/Taiyi-Stable-Diffusion-1B-Chinese-v0.1"
pipe_text2img = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16).to(device)
pipe_img2img = StableDiffusionImg2ImgPipeline(**pipe_text2img.components).to(device)
# pipe_inpaint = StableDiffusionInpaintPipeline.from_pretrained(model_id).to(device) # work
# pipe_inpaint = StableDiffusionInpaintPipeline(**pipe_text2img.components) # not work
# def infer_text2img(prompt, guide, steps, width, height):
# output = pipe_text2img(prompt, width=width, height=height, guidance_scale=guide, num_inference_steps=steps,)
# image = output.images[0]
# return image
def infer_text2img(prompt, guide, steps, width, height, image_in, strength):
if image_in is not None:
init_image = image_in.convert("RGB").resize((width, height))
output = pipe_img2img(prompt, image=init_image, strength=strength, guidance_scale=guide, num_inference_steps=steps)
else:
output = pipe_text2img(prompt, width=width, height=height, guidance_scale=guide, num_inference_steps=steps,)
image = output.images[0]
return image
def infer_inpaint(prompt, guide, steps, width, height, image_in):
init_image = image_in["image"].convert("RGB").resize((width, height))
mask = image_in["mask"].convert("RGB").resize((width, height))
output = pipe_inpaint(prompt, \
init_image=init_image, mask_image=mask, \
width=width, height=height, \
guidance_scale=7.5, num_inference_steps=20)
image = output.images[0]
return image
with gr.Blocks() as demo:
examples = [
["飞流直下三千尺, 疑是银河落九天, 瀑布, 插画"],
["东临碣石, 以观沧海, 波涛汹涌, 插画"],
["孤帆远影碧空尽,惟见长江天际流,油画"],
["女孩背影, 日落, 唯美插画"],
]
with gr.Row():
with gr.Column(scale=1, ):
image_out = gr.Image(label = '输出(output)')
with gr.Column(scale=1, ):
image_in = gr.Image(source='upload', elem_id="image_upload", type="pil", label="参考图(非必须)(ref)")
prompt = gr.Textbox(label = '提示词(prompt)')
submit_btn = gr.Button("生成图像(Generate)")
with gr.Row(scale=0.5 ):
guide = gr.Slider(2, 15, value = 7, step = 0.1, label = '文本引导强度(guidance scale)')
steps = gr.Slider(10, 30, value = 20, step = 1, label = '迭代次数(inference steps)')
width = gr.Slider(384, 640, value = 512, step = 64, label = '宽度(width)')
height = gr.Slider(384, 640, value = 512, step = 64, label = '高度(height)')
strength = gr.Slider(0, 1.0, value = 0.8, step = 0.02, label = '参考图改变程度(strength)')
ex = gr.Examples(examples, fn=infer_text2img, inputs=[prompt, guide, steps, width, height], outputs=image_out)
# with gr.Column(scale=1, ):
# image_in = gr.Image(source='upload', tool='sketch', elem_id="image_upload", type="pil", label="Upload")
# inpaint_prompt = gr.Textbox(label = '提示词(prompt)')
# inpaint_btn = gr.Button("图像编辑(Inpaint)")
# img2img_prompt = gr.Textbox(label = '提示词(prompt)')
# img2img_btn = gr.Button("图像编辑(Inpaint)")
submit_btn.click(fn = infer_text2img, inputs = [prompt, guide, steps, width, height, image_in, strength], outputs = image_out)
# inpaint_btn.click(fn = infer_inpaint, inputs = [inpaint_prompt, width, height, image_in], outputs = image_out)
# img2img_btn.click(fn = infer_img2img, inputs = [img2img_prompt, width, height, image_in], outputs = image_out)
demo.queue(concurrency_count=1, max_size=8).launch()