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webui.py
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#!/usr/bin/env python
# -*- encoding: utf-8 -*-
import random
import gradio as gr
import os
import utils
from PIL import Image
from modules import txt2img, img2img, inpaint
import zipfile
# controlnet #
# from examples.controlnet.gradio_pose2image import process as pose2image
## UI设计 ##
with gr.Blocks() as demo:
# 顶部文字
gr.Markdown("""
# AI绘画
### 开源项目地址：https://github.com/tensorfly-gpu/PPdiffusers-webui
""")
# 暂不支持换模型
with gr.Row():
with gr.Column():
model_name = gr.Dropdown(utils.model_name_list, label="请选择一个基础模型", default="Baitian/momocha", multiselect=False) # 同时作为训练lora的预训练模型
with gr.Column():
lora_name = gr.Dropdown(utils.model_name_list, label="请选择一个lora模型", default="text_encoder_unet_lora.safetensors", multiselect=False)
# 多个tab
with gr.Tabs():
with gr.TabItem("文生图"):
# 一行 两列 左边一列是输入 右边一列是输出
with gr.Row():
with gr.Column(): # 左边一列是输入
txt2img_prompt = gr.Textbox(label="prompt", lines=3, placeholder="请输入正面描述", interactive=True, value=None)
txt2img_negative_prompt = gr.Textbox(label="negative_prompt", lines=2, placeholder="请输入负面描述", interactive=True, value=None)
with gr.Row():
txt2img_sampler = gr.Dropdown(utils.support_scheduler, label="Sampling method", default="DDIM", multiselect=False)
txt2img_steps = gr.Slider(minimum=1, maximum=100, value=50, step=1, label="Sampling steps", interactive=True)
with gr.Row():
txt2img_Image_size = gr.Dropdown(["512x512", "512x768", "768x512", "640x640"], default="512x768", label="Image size", multiselect=False)
# 返回只能显示一张图片, 待修复
# 先用只能一次生成一张图片替代
txt2img_num_images = 1
# num_images = gr.Slider(minimum=1, maximum=5, value=1, step=1, label="Num images", interactive=True)
txt2img_seed = gr.Textbox(label="seed", default="-1", lines=1, placeholder="请输入种子，默认-1")
txt2img_cfg_scale = gr.Slider(minimum=1, maximum=20, value=7, step=0.1, label="CFG Scale", interactive=True)
# 生成、重置按钮（row：行）
with gr.Row():
txt2img_button = gr.Button("生成")
# clear_button = gr.Button("重置")
with gr.Column(): # 右边一列是输出
# 输出框
txt2img_output = gr.Image(type="pil")
with gr.TabItem("图生图"):
# 一行 两列 左边一列是输入 右边一列是输出
with gr.Row():
with gr.Column(): # 左边一列是输入
img2img_prompt = gr.Textbox(label="prompt", lines=3, placeholder="请输入正面描述", interactive=True,
value=None)
img2img_negative_prompt = gr.Textbox(label="negative_prompt", lines=2, placeholder="请输入负面描述",
interactive=True, value=None)
with gr.Row():
img2img_sampler = gr.Dropdown(utils.support_scheduler, label="Sampling method", default="DDIM",
multiselect=False)
img2img_steps = gr.Slider(minimum=1, maximum=100, value=50, step=1, label="Sampling steps",
interactive=True)
with gr.Row():
img2img_Image_size = gr.Dropdown(["512x512", "512x768", "768x512", "640x640", "自动判断"], default="512x768",
label="Image size", multiselect=False)
# 返回只能显示一张图片, 待修复
# 先用只能一次生成一张图片替代
img2img_num_images = 1
# num_images = gr.Slider(minimum=1, maximum=5, value=1, step=1, label="Num images", interactive=True)
img2img_seed = gr.Textbox(label="seed", default="-1", lines=1, placeholder="请输入种子，默认-1")
with gr.Row():
img2img_cfg_scale = gr.Slider(minimum=1, maximum=20, value=7, step=0.1, label="CFG Scale", interactive=True)
img2img_strength = gr.Slider(minimum=0, maximum=1, value=0.5, step=0.01, label="strength",
interactive=True)
img2img_image_init = gr.Image(label="请上传图片")
# 生成、重置按钮（row：行）
with gr.Row():
img2img_button = gr.Button("生成")
# clear_button = gr.Button("重置")
with gr.Column(): # 右边一列是输出
# 输出框
img2img_output = gr.Image(type="pil")
with gr.TabItem("局部重绘"):
# 一行 两列 左边一列是输入 右边一列是输出
with gr.Row():
with gr.Column(): # 左边一列是输入
inpaint_prompt = gr.Textbox(label="prompt", lines=3, placeholder="请输入正面描述", interactive=True,
value=None)
inpaint_negative_prompt = gr.Textbox(label="negative_prompt", lines=2, placeholder="请输入负面描述",
interactive=True, value=None)
with gr.Row():
inpaint_sampler = gr.Dropdown(utils.support_scheduler, label="Sampling method", default="DDIM",
multiselect=False)
inpaint_steps = gr.Slider(minimum=1, maximum=100, value=50, step=1, label="Sampling steps",
interactive=True)
with gr.Row():
inpaint_Image_size = gr.Dropdown(["512x512", "512x768", "768x512", "640x640", "自动判断"], default="512x768",
label="Image size", multiselect=False)
# 返回只能显示一张图片, 待修复
# 先用只能一次生成一张图片替代
inpaint_num_images = 1
# num_images = gr.Slider(minimum=1, maximum=5, value=1, step=1, label="Num images", interactive=True)
inpaint_seed = gr.Textbox(label="seed", default="-1", lines=1, placeholder="请输入种子，默认-1")
with gr.Row():
inpaint_cfg_scale = gr.Slider(minimum=1, maximum=20, value=7, step=0.1, label="CFG Scale", interactive=True)
inpaint_strength = gr.Slider(minimum=0, maximum=1, value=0.5, step=0.01, label="strength",
interactive=True)
# 上传图片，生成图片
with gr.Row():
inpaint_image_mask_init = gr.Image(tool="sketch", label="请上传图片，然后使用鼠标涂抹",
type="numpy")
with gr.Column(): # 右边一列是输出
# 输出框
inpaint_output = gr.Image(type="pil")
inpaint_button = gr.Button("生成")
with gr.TabItem("训练"):
# 多个tab
with gr.Tabs():
# 训练第一种lora
with gr.TabItem("train dreambooth lora"):
# 使用1行2列
with gr.Row():
with gr.Column(): # 左边一列是输入
# dataset通过解压上传的压缩包上传时，同时启动训练
# TODO: 其他参数设置
file_upload = gr.File()
output_text = gr.Textbox()
train_dreambooth_lora_button = gr.Button("开始训练")
with gr.Column(): # 右边一列是输出
# 输出框
test2 = gr.Textbox(label="seed", default="-1", lines=1, placeholder="请输入种子，默认-1")
with gr.TabItem("train text2image lora"):
test3 = gr.Textbox(label="seed", default="-1", lines=1, placeholder="请输入种子，默认-1")
# with gr.TabItem("ControlNet"):
# with gr.Row():
# with gr.Column():
# input_image = gr.Image(source="upload", type="numpy")
# hand = gr.Checkbox(label="detect hand", value=False)
# prompt = gr.Textbox(label="Prompt")
# pose2image_button = gr.Button(label="Run")
# with gr.Accordion("Advanced options", open=False):
# num_samples = gr.Slider(label="Images", minimum=1, maximum=12, value=1, step=1)
# image_resolution = gr.Slider(label="Image Resolution", minimum=256, maximum=768, value=512,
# step=64)
# strength = gr.Slider(label="Control Strength", minimum=0.0, maximum=2.0, value=1.0,
# step=0.01)
# guess_mode = gr.Checkbox(label="Guess Mode", value=False)
# detect_resolution = gr.Slider(
# label="OpenPose Resolution", minimum=128, maximum=1024, value=512, step=1
# )
# ddim_steps = gr.Slider(label="Steps", minimum=1, maximum=100, value=20, step=1)
# scale = gr.Slider(label="Guidance Scale", minimum=0.1, maximum=30.0, value=9.0, step=0.1)
# seed = gr.Slider(label="Seed", minimum=-1, maximum=2147483647, step=1, randomize=True)
# eta = gr.Number(label="eta (DDIM)", value=0.0)
# a_prompt = gr.Textbox(label="Added Prompt", value="best quality, extremely detailed")
# n_prompt = gr.Textbox(
# label="Negative Prompt",
# value="longbody, lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality",
# )
# with gr.Column():
# result_gallery = gr.Gallery(label="Output", show_label=False, elem_id="gallery").style(
# grid=2, height="auto"
# )
# ips = [
# input_image,
# hand,
# prompt,
# a_prompt,
# n_prompt,
# num_samples,
# image_resolution,
# detect_resolution,
# ddim_steps,
# guess_mode,
# strength,
# scale,
# seed,
# eta,
# ]
txt2img_button.click(fn=txt2img,
inputs=[model_name, txt2img_prompt, txt2img_negative_prompt, txt2img_sampler, txt2img_Image_size, txt2img_cfg_scale, txt2img_steps, txt2img_seed],
outputs=txt2img_output)
img2img_button.click(fn=img2img,
inputs=[model_name, img2img_image_init, img2img_prompt, img2img_negative_prompt, img2img_sampler, img2img_Image_size, img2img_strength, img2img_cfg_scale, img2img_steps, img2img_seed],
outputs=img2img_output)
inpaint_button.click(fn=inpaint,
inputs=[model_name, inpaint_image_mask_init, inpaint_prompt, inpaint_negative_prompt, inpaint_sampler, inpaint_Image_size, inpaint_strength, inpaint_cfg_scale, inpaint_steps, inpaint_seed],
outputs=inpaint_output)
train_dreambooth_lora_button.click(
fn=utils.train_dreambooth_lora,
inputs=file_upload,
outputs=output_text)
# pose2image_button.click(fn=pose2image, inputs=ips, outputs=[result_gallery])