pip install gradio
#为了更快安装，可以使用清华镜像源pip install -i https://pypi.tuna.tsinghua.edu.cn/simple gradio

import gradio as gr#输入文本处理程序def greet(name):    return "Hello " + name + "!"#接口创建函数#fn设置处理函数，inputs设置输入接口组件，outputs设置输出接口组件#fn,inputs,outputs都是必填函数demo = gr.Interface(fn=greet, inputs="text", outputs="text")demo.launch()

#执行结果Running on local URL:  http://127.0.0.1:7860
To create a public link, set `share=True` in `launch()`.

gradio app.py

import gradio as grdef greet(name):    return "Hello " + name + "!"demo = gr.Interface(    fn=greet,    # 自定义输入框    # 具体设置方法查看官方文档    inputs=gr.Textbox(lines=3, placeholder="Name Here...",label="my input"),    outputs="text",)demo.launch()

import gradio as gr
def greet(name):    return "Hello " + name + "!"
iface = gr.Interface(    fn=greet,    inputs=gr.inputs.Textbox(lines=2, placeholder="Name Here..."),    outputs="text",)if __name__ == "__main__":    app, local_url, share_url = iface.launch()

import gradio as gr#该函数有3个输入参数和2个输出参数def greet(name, is_morning, temperature):    salutation = "Good morning" if is_morning else "Good evening"    greeting = f"{salutation} {name}. It is {temperature} degrees today"    celsius = (temperature - 32) * 5 / 9    return greeting, round(celsius, 2)demo = gr.Interface(    fn=greet,    #按照处理程序设置输入组件    inputs=["text", "checkbox", gr.Slider(0, 100)],    #按照处理程序设置输出组件    outputs=["text", "number"],)demo.launch()

import numpy as npimport gradio as grdef sepia(input_img):    #处理图像    sepia_filter = np.array([        [0.393, 0.769, 0.189],        [0.349, 0.686, 0.168],        [0.272, 0.534, 0.131]    ])    sepia_img = input_img.dot(sepia_filter.T)    sepia_img /= sepia_img.max()    return sepia_img#shape设置输入图像大小demo = gr.Interface(sepia, gr.Image(shape=(200, 200)), "image")demo.launch()

import gradio as gr
def calculator(num1, operation, num2):    if operation == "add":        return num1 + num2    elif operation == "subtract":        return num1 - num2    elif operation == "multiply":        return num1 * num2    elif operation == "divide":        return num1 / num2
iface = gr.Interface(    calculator,    ["number", gr.inputs.Radio(["add", "subtract", "multiply", "divide"]), "number"],    "number",    live=True,)
iface.launch()

import gradio as gr#一个简单计算器，含实例说明def calculator(num1, operation, num2):    if operation == "add":        return num1 + num2    elif operation == "subtract":        return num1 - num2    elif operation == "multiply":        return num1 * num2    elif operation == "divide":        if num2 == 0:            # 设置报错弹窗            raise gr.Error("Cannot divide by zero!")        return num1 / num2demo = gr.Interface(    calculator,    # 设置输入    [        "number",        gr.Radio(["add", "subtract", "multiply", "divide"]),        "number"    ],    # 设置输出    "number",    # 设置输入参数示例    examples=[        [5, "add", 3],        [4, "divide", 2],        [-4, "multiply", 2.5],        [0, "subtract", 1.2],    ],    # 设置网页标题    title="Toy Calculator",    # 左上角的描述文字    description="Here's a sample toy calculator. Enjoy!",    # 左下角的文字    article = "Check out the examples",)demo.launch()

import gradio as grscores = []def track_score(score):    scores.append(score)    #返回分数top3    top_scores = sorted(scores, reverse=True)[:3]    return top_scoresdemo = gr.Interface(    track_score,    gr.Number(label="Score"),    gr.JSON(label="Top Scores"))demo.launch()

import randomimport gradio as grdef chat(message, history):    history = history or []    message = message.lower()    if message.startswith("how many"):        response = random.randint(1, 10)    elif message.startswith("how"):        response = random.choice(["Great", "Good", "Okay", "Bad"])    elif message.startswith("where"):        response = random.choice(["Here", "There", "Somewhere"])    else:        response = "I don't know"    history.append((message, response))    return history, history#设置一个对话窗chatbot = gr.Chatbot().style(color_map=("green", "pink"))demo = gr.Interface(    chat,    # 添加state组件    ["text", "state"],    [chatbot, "state"],    # 设置没有保存数据的按钮    allow_flagging="never",)demo.launch()

import gradio as grimport numpy as npdef flip(im):    return np.flipud(im)demo = gr.Interface(    flip,    gr.Image(source="webcam", streaming=True),    "image",    live=True)demo.launch()

import gradio as grdef greet(name):    return "Hello " + name + "!"with gr.Blocks() as demo:    #设置输入组件    name = gr.Textbox(label="Name")    # 设置输出组件    output = gr.Textbox(label="Output Box")    #设置按钮    greet_btn = gr.Button("Greet")    #设置按钮点击事件    greet_btn.click(fn=greet, inputs=name, outputs=output)demo.launch()

import numpy as npimport gradio as grdef flip_text(x):    return x[::-1]def flip_image(x):    return np.fliplr(x)with gr.Blocks() as demo:    #用markdown语法编辑输出一段话    gr.Markdown("Flip text or image files using this demo.")    # 设置tab选项卡    with gr.Tab("Flip Text"):        #Blocks特有组件，设置所有子组件按垂直排列        #垂直排列是默认情况，不加也没关系        with gr.Column():            text_input = gr.Textbox()            text_output = gr.Textbox()            text_button = gr.Button("Flip")    with gr.Tab("Flip Image"):        #Blocks特有组件，设置所有子组件按水平排列        with gr.Row():            image_input = gr.Image()            image_output = gr.Image()        image_button = gr.Button("Flip")    #设置折叠内容    with gr.Accordion("Open for More!"):        gr.Markdown("Look at me...")    text_button.click(flip_text, inputs=text_input, outputs=text_output)    image_button.click(flip_image, inputs=image_input, outputs=image_output)demo.launch()

img = gr.Image("lion.jpg").style(height='24', rounded=False)

demo = gr.Interface(...).queue()demo.launch()#或with gr.Blocks() as demo:    #...demo.queue()demo.launch()

import gradio as grimport numpy as npimport time#生成steps张图片，每隔1秒钟返回def fake_diffusion(steps):    for _ in range(steps):        time.sleep(1)        image = np.random.randint(255, size=(300, 600, 3))        yield imagedemo = gr.Interface(fake_diffusion,                    #设置滑窗，最小值为1，最大值为10，初始值为3，每次改动增减1位                    inputs=gr.Slider(1, 10, value=3, step=1),                    outputs="image")#生成器必须要queue函数demo.queue()demo.launch()

import gradio as grdef greet(name):    return "Hello " + name + "!"with gr.Blocks() as demo:    name = gr.Textbox(label="Name")    # 不可交互    # output = gr.Textbox(label="Output Box")    # 可交互    output = gr.Textbox(label="Output", interactive=True)    greet_btn = gr.Button("Greet")    greet_btn.click(fn=greet, inputs=name, outputs=output)demo.launch()

import gradio as grdef welcome(name):    return f"Welcome to Gradio, {name}!"with gr.Blocks() as demo:    gr.Markdown(    """    # Hello World!    Start typing below to see the output.    """)    inp = gr.Textbox(placeholder="What is your name?")    out = gr.Textbox()    #设置change事件    inp.change(fn = welcome, inputs = inp, outputs = out)demo.launch()

import gradio as grdef increase(num):    return num + 1with gr.Blocks() as demo:    a = gr.Number(label="a")    b = gr.Number(label="b")    # 要想b>a，则使得b = a+1    atob = gr.Button("b > a")    atob.click(increase, a, b)    # 要想a>b，则使得a = b+1    btoa = gr.Button("a > b")    btoa.click(increase, b, a)demo.launch()

import gradio as grwith gr.Blocks() as demo:    food_box = gr.Number(value=10, label="Food Count")    status_box = gr.Textbox()    def eat(food):        if food > 0:            return food - 1, "full"        else:            return 0, "hungry"    gr.Button("EAT").click(        fn=eat,        inputs=food_box,        #根据返回值改变输入组件和输出组件        outputs=[food_box, status_box]    )demo.launch()

import gradio as grdef change_textbox(choice):    #根据不同输入对输出控件进行更新    if choice == "short":        return gr.update(lines=2, visible=True, value="Short story: ")    elif choice == "long":        return gr.update(lines=8, visible=True, value="Long story...")    else:        return gr.update(visible=False)with gr.Blocks() as demo:    radio = gr.Radio(        ["short", "long", "none"], label="Essay Length to Write?"    )    text = gr.Textbox(lines=2, interactive=True)    radio.change(fn=change_textbox, inputs=radio, outputs=text)demo.launch()

import gradio as grwith gr.Blocks() as demo:    with gr.Row():        img1 = gr.Image()        text1 = gr.Text()    btn1 = gr.Button("button")demo.launch()

import gradio as grwith gr.Blocks() as demo:    with gr.Row():        text1 = gr.Textbox(label="t1")        slider2 = gr.Textbox(label="s2")        drop3 = gr.Dropdown(["a", "b", "c"], label="d3")    with gr.Row():        # scale与相邻列相比的相对宽度。例如，如果列A的比例为2，列B的比例为1，则A的宽度将是B的两倍。        # min_width设置最小宽度，防止列太窄        with gr.Column(scale=2, min_width=600):            text1 = gr.Textbox(label="prompt 1")            text2 = gr.Textbox(label="prompt 2")            inbtw = gr.Button("Between")            text4 = gr.Textbox(label="prompt 1")            text5 = gr.Textbox(label="prompt 2")        with gr.Column(scale=1, min_width=600):            img1 = gr.Image("test.jpg")            btn = gr.Button("Go")demo.launch()

import gradio as grwith gr.Blocks() as demo:    # 出错提示框    error_box = gr.Textbox(label="Error", visible=False)    # 输入框    name_box = gr.Textbox(label="Name")    age_box = gr.Number(label="Age")    symptoms_box = gr.CheckboxGroup(["Cough", "Fever", "Runny Nose"])    submit_btn = gr.Button("Submit")    # 输出不可见    with gr.Column(visible=False) as output_col:        diagnosis_box = gr.Textbox(label="Diagnosis")        patient_summary_box = gr.Textbox(label="Patient Summary")    def submit(name, age, symptoms):        if len(name) == 0:            return {error_box: gr.update(value="Enter name", visible=True)}        if age < 0 or age > 200:            return {error_box: gr.update(value="Enter valid age", visible=True)}        return {            output_col: gr.update(visible=True),            diagnosis_box: "covid" if "Cough" in symptoms else "flu",            patient_summary_box: f"{name}, {age} y/o"        }    submit_btn.click(        submit,        [name_box, age_box, symptoms_box],        [error_box, diagnosis_box, patient_summary_box, output_col],    )demo.launch()

import gradio as grinput_textbox = gr.Textbox()with gr.Blocks() as demo:    #提供示例输入给input_textbox，示例输入以嵌套列表形式设置    gr.Examples(["hello", "bonjour", "merhaba"], input_textbox)    # render函数渲染input_textbox    input_textbox.render()demo.launch()

import gradio as gr#修改blocks的背景颜色with gr.Blocks(css=".gradio-container {background-color: red}") as demo:    box1 = gr.Textbox(value="Good Job")    box2 = gr.Textbox(value="Failure")demo.launch()

import gradio as gr# 这里用的是id属性设置with gr.Blocks(css="#warning {background-color: red}") as demo:    box1 = gr.Textbox(value="Good Job", elem_id="warning")    box2 = gr.Textbox(value="Failure")    box3 = gr.Textbox(value="None", elem_id="warning")demo.launch()

demo.launch(share=True)

#show_error为True表示在控制台显示错误信息。demo.launch(server_name='0.0.0.0', server_port=8080, show_error=True)

demo.launch(auth=("admin", "pass1234"))

#账户和密码相同就可以通过def same_auth(username, password):    return username == passworddemo.launch(auth=same_auth,auth_message="username and password must be the same")

#!pip install gradio, ultralytics, transformers, torchkeras

import gradio as gr from transformers import pipeline pipe = pipeline("text-classification") def clf(text):    result = pipe(text)    label = result[0]['label']    score = result[0]['score']    res = {label:score,'POSITIVE' if label=='NEGATIVE' else 'NEGATIVE': 1-score}    return res  demo = gr.Interface(fn=clf, inputs="text", outputs="label")gr.close_all()demo.launch(share=True)

import gradio as gr import pandas as pd from ultralytics import YOLOfrom skimage import datafrom PIL import Image model = YOLO('yolov8n-cls.pt')def predict(img):    result = model.predict(source=img)    df = pd.Series(result[0].names).to_frame()    df.columns = ['names']    df['probs'] = result[0].probs    df = df.sort_values('probs',ascending=False)    res = dict(zip(df['names'],df['probs']))    return resgr.close_all() demo = gr.Interface(fn = predict,inputs = gr.Image(type='pil'), outputs = gr.Label(num_top_classes=5),                     examples = ['cat.jpeg','people.jpeg','coffee.jpeg'])demo.launch()

import gradio as gr import pandas as pd from skimage import datafrom ultralytics.yolo.data import utils  model = YOLO('yolov8n.pt') #load class_namesyaml_path = str(Path(ultralytics.__file__).parent/'datasets/coco128.yaml') class_names = utils.yaml_load(yaml_path)['names']
def detect(img):    if isinstance(img,str):        img = get_url_img(img) if img.startswith('http') else Image.open(img).convert('RGB')    result = model.predict(source=img)    if len(result[0].boxes.boxes)>0:        vis = plots.plot_detection(img,boxes=result[0].boxes.boxes,                     class_names=class_names, min_score=0.2)    else:        vis = img    return vis    with gr.Blocks() as demo:    gr.Markdown("# yolov8目标检测演示")     with gr.Tab("捕捉摄像头喔"):        in_img = gr.Image(source='webcam',type='pil')        button = gr.Button("执行检测",variant="primary")         gr.Markdown("## 预测输出")        out_img = gr.Image(type='pil')         button.click(detect,                     inputs=in_img,                      outputs=out_img)            gr.close_all() demo.queue(concurrency_count=5)demo.launch()

#!pip install -U torchkeras

import torchkeras from torchkeras.data import download_baidu_pictures download_baidu_pictures('猫咪表情包',100)
import gradio as grfrom PIL import Imageimport time,osfrom pathlib import Path base_dir = '猫咪表情包'selected_dir = 'selected'files = [str(x) for x in          Path(base_dir).rglob('*.jp*g')          if 'checkpoint' not in str(x)]def show_img(path):    return Image.open(path)def fn_before(done,todo):    ...    return done,todo,path,imgdef fn_next(done,todo):    ...    return done,todo,path,imgdef save_selected(img_path):    ...    return msg def get_default_msg():    ...    return msg        with gr.Blocks() as demo:    with gr.Row():        total = gr.Number(len(files),label='总数量')        with gr.Row(scale = 1):            bn_before = gr.Button("上一张")            bn_next = gr.Button("下一张")        with gr.Row(scale = 2):            done = gr.Number(0,label='已完成')            todo = gr.Number(len(files),label='待完成')    path = gr.Text(files[0],lines=1, label='当前图片路径')    feedback_button = gr.Button("选择图片",variant="primary")    msg = gr.TextArea(value=get_default_msg,lines=3,max_lines = 5)    img = gr.Image(value = show_img(files[0]),type='pil')        bn_before.click(fn_before,                 inputs= [done,todo],                  outputs=[done,todo,path,img])    bn_next.click(fn_next,                 inputs= [done,todo],                  outputs=[done,todo,path,img])    feedback_button.click(save_selected,                         inputs = path,                         outputs = msg                         )
demo.launch()