Gradio机器学习模型快速部署工具quickstart

import numpy as np
import gradio as gr
def sepia(input_img):
    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
demo = gr.Interface(sepia, gr.Image(shape=(200, 200)), "image")
demo.launch()

gr.Image(type="filepath", shape=...)

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

import numpy as np
import gradio as gr
# 1.文字翻转
def flip_text(x):
    return x[::-1]
# 2.图像翻转
def flip_image(x):
    return np.fliplr(x)
with gr.Blocks() as demo:
    # 3.添加markdown组件
    gr.Markdown("Flip text or image files using this demo.")
    # 4.添加Tab
    with gr.Tab("Flip Text"):
        text_input = gr.Textbox()
        text_output = gr.Textbox()
        text_button = gr.Button("Flip")
    with gr.Tab("Flip Image"):
        with gr.Row():
            image_input = gr.Image()
            image_output = gr.Image()
        image_button = gr.Button("Flip")
    # 5.添加Accordion
    with gr.Accordion("Open for More!"):
        gr.Markdown("Look at me...")
    # 6.添加2个按钮
    text_button.click(flip_text, inputs=text_input, outputs=text_output)
    image_button.click(flip_image, inputs=image_input, outputs=image_output)
demo.launch()