UI界面

PyQt

首先，通过Pip安装PyQt组件。

> pip install pyqt6
> pip install pyqt6-tools

注意：目前pyqt6和pyqt6-tools只能在Python3.9版本中安装成功，用最新的版本中可能会出现依赖冲突。

然后，在PyCharm中添加外部工具。

在PyCharm中添加外部工具

此处路径为${anaconda3}/envs/dev-3.9/lib/python3.9/site-packages/qt6_applications/Qt/bin/Designer.app。

创建新的Python文件，然后单击鼠标右键，在弹出的菜单中选择External Tools -> pyqt。

选择PyQt外部工具

打开后，就会出现如下的PyQt界面。

PyQt界面

以和PyQt同样的方式配置pyuic。

配置pyuic

输入的内容分别如下。

• Program：${anaconda3}/envs/dev-3.9/bin/pyuic6。

• Arguments：-o $FileNameWithoutExtension$.py $FileName$。

• Working dirctory：$FileDir$。

在PyQt界面新建一个MainWindow，将它保存到和main.py相同的目录中，并命名为qttest.ui。

在qttest.ui文件上单击鼠标右键，通过pyuic来自动生成对应的qttest.py文件。

自动生成python文件

之后在main.py中输入如下代码。

from qttest import Ui_MainWindow
import sys
from PyQt6.QtWidgets import QApplication, QMainWindow

class TestWindow(QMainWindow, Ui_MainWindow):
    def __init__(self, parent=None):
        super(TestWindow, self).__init__(parent)
        self.setupUi(self)

if __name__ == '__main__':
    app = QApplication(sys.argv)
    ui = TestWindow()
    ui.show()
    sys.exit(app.exec())

运行后出现可视化界面。

生成的UI界面

用PyQt重新打开qttest.ui文件，然后拖入PushButton和Label两个组件到窗口中，分别命名为imageLabel和openFileButton。

修改UI界面

之后用pyuic重新生成对应的qttest.py文件。

在main.py添加实现功能的代码。

from qttest import Ui_MainWindow
import sys
from PyQt6.QtWidgets import QApplication, QMainWindow, QFileDialog
from PyQt6 import QtGui

class TestWindow(QMainWindow, Ui_MainWindow):
    def __init__(self, parent=None):
        super(TestWindow, self).__init__(parent)
        self.setupUi(self)
        self.openFileButton.clicked.connect(self.openFile)

    def openFile(self):
        self.filename, _ = QFileDialog.getOpenFileName(self, "打开文件", ".", "图片文件(*.jpg *.png)")
        pixmap = QtGui.QPixmap(self.filename).scaled(self.imageLabel.width(), self.imageLabel.height())
        self.imageLabel.setPixmap(pixmap)

if __name__ == '__main__':
    app = QApplication(sys.argv)
    ui = TestWindow()
    ui.show()
    sys.exit(app.exec())

运行后效果如下图。

运行效果

Gradio

大名鼎鼎的Stable Diffusion就是通过Gradio实现文生图应用的。

基于Gradio构建的Stable Diffusion

首先，通过Pip安装Gradio。

> pip install gradio

然后，就可以编写下面的代码了。

import gradio as gr

def greet(name, intensity):
    return "Hello, " + name + "!" * int(intensity)

hello = gr.Interface(
    fn = greet,
    inputs=["text", "slider"],
    outputs=["text"],
)

# 可以在launch()中添加端口号和是否在公网上显示链接
# 如果加上了share=True，那么会显示一个72小时内有效的公网链接
hello.launch(server_port=8080)

运行程序后输出结果如下。

* Running on local URL: http://127.0.0.1:8080
* Running on public URL: https://xxxxxxxxxxxxxxxxx.gradio.live

打开浏览器，界面显示如下。

基于Gradio的应用

更多关于Gradio的代码如下。

import gradio as gr
import numpy as np
import matplotlib.pyplot as plt
from PIL.ImageOps import scale

def func():
    pass

def button_clicked(name):
    return f"Hello {name}"

# 点击事件
with gr.Blocks() as clickEvent:
    text_input = gr.Textbox("点击按钮后的反馈将显示在这里")
    button = gr.Button("点击我")
    button.click(fn=lambda: button_clicked("test"), outputs=[text_input])

# 输出matplotlib
def output_matplotlib():
    x = np.linspace(0, 10, 100)
    fig, ax = plt.subplots()
    ax.plot(x, np.sin(x), label='sin')
    ax.plot(x, np.cos(x), label='cos')
    ax.legend()
    return fig

def gallery_list():
    images = [
        "文章封面1.png",
        "文章封面2.png",
        "文章封面1.png",
        "文章封面2.png",
        "文章封面1.png",
        "文章封面2.png",
        "文章封面1.png",
        "文章封面2.png",
        "文章封面1.png",
        "文章封面2.png",
    ]
    # 给每张图片加上标签
    results = [(img, f"图片 {i + 1}") for i, img in enumerate(images)]
    return results

'''
绘图界面
'''
image = gr.Interface(
    fn=output_matplotlib,
    inputs=None,
    outputs=gr.Plot()
)

'''
画廊界面
'''
gallery = gr.Interface(
    fn=gallery_list,
    inputs=None,
    outputs=gr.Gallery(label="图片列表", columns=4)
)

'''
常见组件界面
'''
normal = gr.Interface(
    fn=func,
    # 常用输入
    inputs=[
        # 常用文本输入框
        gr.Text(label="账号", placeholder="请输入账号"),
        gr.Text(label="密码", placeholder="请输入密码", type="password"),
        gr.Text(label="邮箱", placeholder="请输入邮箱", type="email"),
        gr.Textbox(label="个人信息", lines=3, max_lines=5, placeholder="请填写个人信息"),
        gr.TextArea(label="个人介绍", lines=3, max_lines=5, placeholder="请输入个人介绍"),
        # 常用数字输入框
        gr.Number(label="年龄", precision=0),
        gr.Number(label="身高（CM）", precision=2),
        gr.Number(label="资产", precision=2, value=10000),
        # 不可编辑
        gr.Number(label="资产", precision=2, value=10000, interactive=False),
        gr.Slider(label="体重", minimum=0, maximum=100, step=1),
        gr.Slider(label="血型", minimum=1, maximum=4, step=1, value=3, info="1:A型，2:B型，3:O型，4:AB型"),
        # 勾选框
        gr.Checkbox(label="是否同意"),
        # 单选框
        gr.Radio(label="性别", choices=["男", "女", "保密"], type="index"),
        # 多选框
        gr.CheckboxGroup(label="爱好", choices=["足球", "篮球", "游泳", "跑步"]),
        # 下拉框
        gr.Dropdown(label="城市",
                    choices=["北京", "上海", "广州", "深圳", "成都", "西安", "武汉", "郑州", "重庆", "天津", "昆明",
                             "杭州", "南京", "珠海"]),
        # 文件选择器（允许上传文件夹）
        gr.File(label="上传文件", file_count="directory", file_types=None),
        # 图片选择器
        gr.Image(label="上传图片", width=224, height=224),
        # 视频选择器
        gr.Video(label="上传视频", width=224, height=224),
        # 按钮
        # 可以给按钮设置icon
        gr.Button("点击我", icon="这里设置图标资源路径"),
        gr.Button("提交", variant="primary"),
        gr.Button("重置", variant="secondary"),
        gr.Button("取消", variant="stop"),
        gr.Button("返回", variant="huggingface"),
    ],
    # 常用输出
    outputs=[
        gr.Text(label="输出", placeholder="这里显示输出内容"),
        gr.Textbox(label="输出", lines=3, max_lines=5, placeholder="这里显示输出内容"),
        gr.TextArea(label="输出", lines=3, max_lines=5, placeholder="这里显示输出内容"),
    ],
)

'''
行排版
'''
with gr.Blocks() as row:
    with gr.Row():
        # 通过scale参数调整组件的宽度占比
        input1 = gr.Text(label="输入", placeholder="请输入内容", scale=2),
        button1 = gr.Button("欢迎", variant="primary", scale=3)
        text1 = gr.Text(label="输出", placeholder="显示输出内容", scale=5)

    with gr.Row():
        input2 = gr.Text(label="输入", placeholder="请输入内容", scale=5),
        button2 = gr.Button("欢迎", variant="primary", scale=3)
        text2 = gr.Text(label="输出", placeholder="显示输出内容", scale=2)

    button1.click(fn=button_clicked, inputs=input1, outputs=text1)
    button2.click(fn=button_clicked, inputs=input2, outputs=text2)

'''
列排版
'''
with gr.Blocks() as column:
    with gr.Row():
        with gr.Column(scale=5):
            input11 = gr.Textbox(label="提示词", lines=2, placeholder="请输入提示词"),
            input21 = gr.Textbox(label="反向提示词", lines=2, placeholder="请输入反向提示词"),
        with gr.Column(scale=2):
            button11 = gr.Button(">>>"),
            button21 = gr.Button("保存"),
            button31 = gr.Button("文件"),
            button41 = gr.Button("删除"),
        with gr.Column(scale=3):
            button51 = gr.Button("生成", variant="primary"),
            with gr.Row():
                dropbox11 = gr.Dropdown(label="选择样式", choices=["样式1", "样式2", "样式3"]),
                dropbox21 = gr.Dropdown(label="选择条件", choices=["条件1", "条件2", "条件3"]),

'''
标签排版
'''
with gr.Blocks() as tab:
    with gr.Tab("文生图"):
        with gr.Blocks() as column2:
            with gr.Row():
                with gr.Column(scale=5):
                    input12 = gr.Textbox(label="提示词", lines=2, placeholder="请输入提示词"),
                    input22 = gr.Textbox(label="反向提示词", lines=2, placeholder="请输入反向提示词"),
                with gr.Column(scale=2):
                    button12 = gr.Button(">>>"),
                    button22 = gr.Button("保存"),
                    button32 = gr.Button("文件"),
                    button42 = gr.Button("删除"),
                with gr.Column(scale=3):
                    button52 = gr.Button("生成", variant="primary"),
                    with gr.Row():
                        dropbox12 = gr.Dropdown(label="选择样式", choices=["样式1", "样式2", "样式3"]),
                        dropbox22 = gr.Dropdown(label="选择条件", choices=["条件1", "条件2", "条件3"]),
    with gr.Tab("图生图"):
         pass
    with gr.Tab("文生语音"):
         pass
    with gr.Tab("文生视频"):
         pass
    with gr.Tab("模型训练"):
         pass
    with gr.Tab("设置"):
         pass

'''
折叠排版
'''
with gr.Blocks() as block:
    with gr.Accordion("模型参数", open=False):
        gr.Textbox(label="提示词", lines=2, placeholder="请输入提示词"),
        gr.Textbox(label="反向提示词", lines=2, placeholder="请输入反向提示词"),
        gr.Textbox(label="步数", lines=2, placeholder="请输入步数"),
        gr.Textbox(label="学习率", lines=2, placeholder="请输入学习率"),

# 启动点击事件测试
# clickEvent.launch(server_port=8080)

# 启动绘图输出测试
# image.launch(server_port=8080)

# 启动画廊输出测试
# gallery.launch(server_port=8080)

# 启动常见组件测试
# normal.launch(server_port=8080)

# 行排版测试
# row.launch(server_port=8080)

# 列排版测试
# column.launch(server_port=8080)

# 标签排版测试
# tab.launch(server_port=8080)

# 折叠排版测试
block.launch(server_port=8080)

仿Stable Diffusion界面

'''
    仿Stable Diffusion界面
'''
import gradio as gr

with gr.Blocks() as stable_diffusion:
    # 行布局：模型选择
    with gr.Row():
        gr.Dropdown(label="stable diffusion模型", choices=["stable-diffusion-v1-5", "stable-diffusion-2-1-base", "stable-diffusion-2-1"])
        gr.Dropdown(label="外挂VAE模型", choices=["VAE1", "VAE2", "VAE3"]),
        gr.Slider(label="CLIP终止层数", minimum=0, maximum=100, step=1, value=10)

    # 标签布局
    with gr.Tab("文生图"):
        with gr.Row():
            with gr.Column(scale=4):
                prompt = gr.Textbox(label="提示词", lines=2)
                negative_prompt = gr.Textbox(label="负提示词", lines=2)
            with gr.Column(scale=2):
                gr.Button("生成图片", variant="primary")
                with gr.Row():
                    gr.Button("下载", variant="secondary")
                    gr.Button("保存", variant="secondary")
                    gr.Button("删除", variant="secondary")
                gr.Dropdown(label="stable diffusion模型", choices=["stable-diffusion-v1-5", "stable-diffusion-2-1-base", "stable-diffusion-2-1"])

        # 子标签布局
        with gr.Tab("生成"):
            with gr.Row():
                with gr.Column():
                    gr.Slider(label="采样步数", minimum=1, maximum=100, step=1, value=8)
                    gr.Radio(label="采样方法", choices=[
                        "DPM++2M Karras", "DPM++ SDE Karras", "DPM++2M SDE Exponential", "DPM++2M SDE Karras", "Euler a",
                        "Euler", "LMS", "Heun", "DPM2", "DPM2 a", "DPM++2M", "DPM++2M SDE", "DPM++ SDE", "DPM fast",
                        "DPM adaptive", "LMS Karras", "DPM2 Karras", "DPM2 a Karras", "DDIM", "PLMS", "UniPC", "VLM",
                        "K-LMS", "K-Euler a", "K-Euler", "K-Heun", "K-DPM2", "K-DPM2 a", "K-DPM++2M", "K-DPM++2M SDE",
                        "K-DPM++ SDE", "K-DPM fast", "K-DPM adaptive", "K-LMS Karras", "K-DPM2 Karras", "K-DPM2 a Karras",
                        "K-DDIM", "K-PLMS", "K-UniPC", "K-VLM"
                    ], type="index", value=0)
                    # 折叠布局
                    with gr.Accordion("高分辨率修复"):
                        with gr.Row():
                            gr.Dropdown(label="放大算法", choices=["SDXL", "SDXL Refiner", "SDXL VAE", "SDXL VAE Refiner"])
                            gr.Slider(label="高分迭代步数")
                            gr.Slider(label="重绘幅度")
                        with gr.Row():
                            gr.Slider(label="放大倍数")
                            gr.Slider(label="将宽度调整为")
                            gr.Slider(label="将高度调整为")
                    # 折叠布局
                    with gr.Accordion("Refiner"):
                        with gr.Row():
                            gr.Dropdown(label="模型",
                                        choices=["SDXL", "SDXL Refiner", "SDXL VAE", "SDXL VAE Refiner"])
                            gr.Slider(label="切换时机")
                    with gr.Row():
                        with gr.Column(scale=2):
                            gr.Slider(label="宽度", minimum=1, maximum=1000, step=1, value=512)
                            gr.Slider(label="高度", minimum=1, maximum=1000, step=1, value=512)
                        with gr.Column(scale=1, min_width=1):
                            gr.Slider(label="总批次", minimum=1, maximum=100, step=1, value=10, min_width=1)
                            gr.Slider(label="单批数量", minimum=1, maximum=100, step=1, value=10, min_width=1)
                    gr.Slider(label="提示词引导系数", minimum=0, maximum=100, step=1, value=0)
                with gr.Column():
                    gr.Gallery(label="图片", value=[
                        "文章封面1.png",
                        "文章封面2.png",
                        "文章封面1.png",
                        "文章封面2.png",
                        "文章封面1.png",
                        "文章封面2.png",
                        "文章封面1.png",
                        "文章封面2.png",
                        "文章封面1.png",
                        "文章封面2.png",
                    ])
                    with gr.Row():
                        gr.Button("发送到重绘", variant="secondary")
                        gr.Button("发送到后期处理", variant="secondary")
                        gr.Button("下载", variant="secondary")
                    gr.Textbox(label="图像信息", lines=5)
        with gr.Tab("嵌入式"):
            pass
        with gr.Tab("超网络"):
            pass
        with gr.Tab("模型"):
            pass
        with gr.Tab("LoRA"):
            pass

    with gr.Tab("图生图"):
        pass
    with gr.Tab("后期处理"):
        pass
    with gr.Tab("PNG图片信息"):
        pass
    with gr.Tab("模型融合"):
        pass
    with gr.Tab("训练"):
        pass
    with gr.Tab("无边图像浏览"):
        pass
    with gr.Tab("图生图"):
        pass

stable_diffusion.launch(server_port=8080)

完成后的效果如下图所示。

仿Stable Diffusion界面

---

感谢支持

更多内容，请移步《超级个体》。