1、image  图片

import gradio as gr
import numpy as np

def imgdeal(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


def imagetest():
    #shape设置输入图像大小
    demo = gr.Interface(imgdeal, gr.Image(shape=(200, 200)), "image")
    demo.launch()


if __name__ == '__main__':
    imagetest()

 2、audio 音频

import gradio as gr
import librosa


def audio_duration_interface(audio):
    duration = librosa.get_duration(filename=audio)
    return f"The duration of the audio is: {duration} seconds."

def audiotest():
    gr.Interface(fn=audio_duration_interface, inputs=gr.Audio(type="filepath"), outputs=gr.Text()).launch()


if __name__ == '__main__':
    audiotest()

3、vedio 视频

def mymodel(input_video):
    print(type(input_video),input_video)
    return input_video
    # 返回读取的视频

def vediotest():
    # 定义输入和输出界面，使用Video输入和Video输出
    input_interface = gr.Video(label="上传MP4视频或调取摄像头")
    # output_interface = [gr.Image(label="输出图像",show_download_button=True) ,gr.Video(label="输出视频",show_download_button=True)]
    output_interface = gr.Video(label="输出视频",format='mp4')
    
    
    # 设置标题和解释说明
    title = "视频姿态检测模型"
    description = "该模型接受MP4视频作为输入,并输出相同的视频。您可以上传自己的视频，或者使用摄像头录制。"
    
    # 启动Gradio界面
    demo=gr.Interface(mymodel, inputs=input_interface, outputs=output_interface , title=title, description=description)
    demo.launch()


if __name__ == '__main__':
    vediotest()