import gradio as gr
import pulp
import pandas as pd
import openpyxl
import requests
import os
os.system('pip install paddlepaddle')
os.system('pip install paddleocr')
from paddleocr import PaddleOCR, draw_ocr
from PIL import Image
import torch
import re
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import numpy as np
html_code='''
'''
ht_text='''
'''
demo = gr.Blocks(css='''
#chedan {-webkit-transition-duration: 0.4s; transition-duration: 0.4s; border-radius: 40%}
#chedan:hover {background-color: #4CAF50; color: white;}
#chedan:active {background-color: #3e8e41; box-shadow: 0 5px #666; transform: translateY(4px);}
''')
def fx1(x):
return f"欢迎练习Gradio, {x}!"
def fx2(x,y):
m=pulp.LpProblem()
x=list(map(int,x.split(',')))
t=[pulp.LpVariable('t'+str(i),cat=pulp.LpBinary) for i in range(len(x))]
m+=pulp.lpDot(x,t)
m+=(pulp.lpDot(x,t)==y)
m.solve()
resu={'data':[x[i] for i in range(len(t)) if pulp.value(t[i])]}
return resu
def fx3(x):
df=pd.read_excel(x,header=0,engine='openpyxl')
return df
def fx4(x):
url_s="https://tts.baidu.com/text2audio?tex="+x+"&cuid=baike&lan=ZH&ie=utf-8&ctp=1&pdt=301&vol=9&rate=32&per=0"
return "点击音频文件 [voice]("+url_s+")"
def fx5():
return html_code
def fx6(img, lang):
ocr = PaddleOCR(use_angle_cls=True, lang={'中文':'ch','英文':'en','法文':'fr','德文':'german','韩文':'korean','日文':'japan'}[lang],use_gpu=False)
img_path = img.name
result = ocr.ocr(img_path, cls=True)
image = Image.open(img_path).convert('RGB')
boxes = [line[0] for line in result]
txts = [line[1][0] for line in result]
scores = [line[1][1] for line in result]
im_show = draw_ocr(image, boxes, txts, scores,
font_path='simfang.ttf')
im_show = Image.fromarray(im_show)
im_show.save('result.jpg')
return 'result.jpg',list(zip(txts))
def fx7(x,y):
res=re.findall(r'{0}'.format(y),x)
return res
def fx8(x,y,z):
res=re.sub(r'{0}'.format(x),y,z)
return res
def plot(v, a):
g = 9.81
theta = a / 180 * 3.14
tmax = ((2 * v) * np.sin(theta)) / g
timemat = tmax * np.linspace(0, 1, 40)[:, None]
x = (v * timemat) * np.cos(theta)
y = ((v * timemat) * np.sin(theta)) - ((0.5 * g) * (timemat**2))
fig = plt.figure()
plt.scatter(x=x, y=y, marker=".")
plt.xlim(0, 100)
plt.ylim(0, 60)
return fig
def fx9(x):
pd.options.plotting.backend='matplotlib'
plt.close('all')
ax = x.plot(x='数据1',y='数据2',kind='bar',title='chinese word error!', color=["red","green","purple"])
ax.table(cellText=df.values,colLabels=df.columns,loc='bottom',colLoc='center')
return ax.get_figure()
with demo:
gr.Markdown(
"""
# WEB APP测试应用!
