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利用nicegui开发ai工具示例

news 2025/9/1 12:33:34

在这里插入图片描述

from fastapi import FastAPI
import uvicorn
from nicegui import uiclass PipRequirement:def __init__(self):ui.label("依赖安装与依赖展示")class BasicSettings:def __init__(self):self.project_select = ui.select(["test"], label="项目选择").props('filled color=green')ui.separator()# self.model_project_name= ui.input(placeholder="")self.model_name = ui.input(placeholder="yolov5", label="模型名称").props('filled color=green')self.model_name_on_jfrog = ui.input(placeholder="yolov5-op13-fp32", label="模型jfrog名称").props('filled color=green')self.model_name_on_xnas = ui.input(placeholder="pytorch_model_tops_engine.bin", label="模型xnas名称").props('filled color=green')self.jfrog_dir = ui.input(placeholder="enflame_model_zoo/official/aigc/xx/xx",label="模型jfrog上传onnx的路径").props('filled color=green')self.xnas_dir = ui.input(placeholder="inference/algo_test/xx/xx", label="模型xnas上传engine的路径").props('filled color=green')self.save_btn = ui.button("保存基本配置").props('inline color=green').style("width: 100%;")self.clone_btn = ui.button("从当前项目中克隆出新项目").props('inline color=green').style("width: 100%;")class ModelInstance:def __init__(self):example = """
from controlnet_aux import LineartDetector\n
model = LineartDetector.from_pretrained("lllyasviel/Annotators").model        
"""project_select = ui.select(["test"], label="项目选择").props('filled color=green')ui.separator()with ui.label("示例代码参考"):ui.code(content=example)editor = ui.editor(placeholder='# 请在这里写模型实例,要求必须含有model')save_btn = ui.button("保存模型实例").style("width: 100%;")class MainPage:def __init__(self):with ui.header() \.style('box-shadow: 0 2px 4px rgba(0, 0, 0, 0.1)'):with ui.row().classes('max-[1050px]:hidden'):ui.button("重置数据").props("text").classes(replace='text-lg text-white')ui.button("ai 模型转换可视化工具").classes(replace='text-lg text-white').disable()with ui.tabs().classes('w-full') as tabs:basic_settings_ = ui.tab('基本设置')model_instance_ = ui.tab('模型实例配置')model_onnx_export_ = ui.tab('模型导出onnx')model_onnx_topsideas_ = ui.tab('模型onnx精度验证topsideas')model_onnx_build_engine_ = ui.tab('模型onnx编图engine')model_onnx_upload_ = ui.tab('模型onn及weight上传jfrog以及开发者文档上传')model_engine_upload_ = ui.tab('模型engine上传xnas')env_data_ = ui.tab('环境依赖展示')with ui.tab_panels(tabs, value=basic_settings_).classes('w-full h-full') as tab_panels:with ui.tab_panel(basic_settings_):BasicSettings()with ui.tab_panel(model_instance_):ModelInstance()with ui.tab_panel(model_onnx_export_):ui.label('model_onnx_export tab')with ui.tab_panel(model_onnx_topsideas_):ui.label('model_onnx_test tab')with ui.tab_panel(model_onnx_build_engine_):ui.label('model_onnx_test tab')with ui.tab_panel(model_onnx_upload_):ui.label('model_onnx_test tab')with ui.tab_panel(model_engine_upload_):ui.label('model_onnx_test tab')with ui.tab_panel(env_data_):ui.label('model_onnx_test tab')# app = FastAPI()# frontend(app)
# if __name__ == '__main__':
#     uvicorn.run("main:app", reload=True)
MainPage()
ui.run(reload=False)```