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python学习交流Q群：906715085###from __future__ import print_functionfrom PIL import Imagefrom PIL import ImageFontfrom PIL import ImageDrawimport osimport shutilimport time# %% 要生成的文本label_dict = {0: '0

package com.example.test2;import androidx.appcompat.app.AppCompatActivity;import android.os.Bundle;import android.text.method.HideReturnsTransformationMethod;import android.text.method.PasswordTransfo

# -*- coding: utf-8-*-import uiautomation as autoimport timeimport subprocess# subprocess.Popen('C:\Program Files\Google\Chrome\Application\chrome.exe')time.sleep(2)start_time = time.time()pri

import sysimport cv2import mathimport timeimport threadingimport numpy as npimport HiwonderSDK.yaml_handle as yaml_handleif sys.version_info.major == 2:    print('Please run th

__author__ = 'marble_xu'import osimport jsonfrom abc import abstractmethodimport pygame as pgfrom . import constants as cclass State():    def __init__(self):  &n

import warnings# 忽视警告warnings.filterwarnings('ignore')import osimport matplotlibimport cv2 as cvimport numpy as npimport matplotlib.pyplot as pltfrom tensorflow.keras.callbacks import ModelChe

import java.awt.BorderLayout;import java.awt.Color;import java.awt.Font;import java.awt.GraphicsEnvironment;import java.awt.event.ActionEvent;import java.awt.event.ActionListener;import javax.swing.JB

# 这里是导入依赖，需要这些库import mathimport sysimport timeimport torchimport win32apiimport win32conimport win32guifrom PyQt5.QtWidgets import QApplicationfrom pynput.mouse import Controllerimport mouse#这里这俩clas

import requestsfrom bs4 import BeautifulSoupfrom pandas import DataFrame'''    最后成功提取了    '电影排名','电影名','上映时间','导演',&

from sklearn.decomposition import PCAimport numpy as npfrom sklearn.svm import SVCimport matplotlib.pyplot as pltfrom sklearn.model_selection import train_test_splitfrom sklearn.decomposition import P

import pygamefrom pygame.locals import *import pygameimport sysimport asyncioimport timeimport randomclass Player(pygame.sprite.Sprite):    #粽子对象    def __init_

if __name__ == '__main__':"""    opt模型主要参数解析：    --weights：初始化的权重文件的路径地址    --cfg：模型yaml文件的路径地址   &nbs

__author__ = 'marble_xu'import osimport jsonfrom abc import abstractmethodimport pygame as pgfrom . import constants as cclass State():    def __init__(self):  &n

import osimport pandas as pdimport requests#第一步：获取所有宝可梦的编号和名字#爬虫优化，超时重试def get_html(url):    i = 0    #最多重连5次    while i <= 5: &nbsp

import pygameclass Bg(pygame.sprite.Sprite):    def __init__(self):        super(Bg, self).__init__()      &nb

import numpy as npimport PILimport PIL.Imageimport scipyimport scipy.ndimageimport dlibdef get_landmark(filepath, predictor):    """get landmark with dlib &nbsp

import timeimport requests  # 数据请求模块import re  # 正则表达式模块import jsonimport pprintfor page in range(3, 29):    print(f'正在采集第{page}页的数据')    time

from turtle import *def go_to(x, y):    up()    goto(x, y)    down()def small_Circle(size):  # 函数用于绘制心的小圆    speed(

def loadModel(self,model_path = RPN_BATCH_PATH):        """        从model_path中加载模型   &nbs

#-----检测、校验并输出结果-----import cv2#准备好识别方法recognizer = cv2.face.LBPHFaceRecognizer_create()#使用之前训练好的模型recognizer.read('trainner/trainner.yml')#再次调用人脸分类器cascade_path = "haarcascade_frontalfac