PureMath86

PureMath86

#Refer http://craiget.com/extracting-table-data-from-pdfs-with-ocr/
import Image, ImageOps
import subprocess, sys, os, glob

# minimum run of adjacent pixels to call something a line
H_THRESH = 300
V_THRESH = 300

def get_hlines(pix, w, h):
    """Get start/end pixels of lines containing horizontal runs of at least THRESH black pix"""

PureMath86

#!/usr/bin/env python
# -*- coding: utf-8 -*-

from pynput.mouse import Listener
import logging
from importlib import reload

reload(logging)

logging.basicConfig(filename="mouse_log.txt", 

PureMath86

#!/usr/bin/env python
# -*- coding: utf-8 -*-

from pynput.keyboard import Key, Listener
import logging
from importlib import reload

log_dir = ""

reload(logging)

PureMath86

import pyautogui

def mouse_now():
    print('Press Ctrl-C to quit.')
    
    try:
        while True:
            # Get and print the mouse coordinates.
            x, y = pyautogui.position()
            positionStr = 'X: ' + str(x).rjust(4) + ' Y: ' + str(y).rjust(4)

PureMath86

This configuration worked for me, hope it helps

It is based on: https://becominghuman.ai/deep-learning-gaming-build-with-nvidia-titan-xp-and-macbook-pro-with-thunderbolt2-5ceee7167f8b

and on: https://stackoverflow.com/questions/44744737/tensorflow-mac-os-gpu-support

Hardware

PureMath86

import pandas as pd
import pyperclip
import io


def frame_clipboard():
    s = pyperclip.paste()
    clip_df = pd.read_table(io.StringIO(s))
    return clip_df

PureMath86

API workthough

1. Open a browser

   # start an instance of firefox with selenium-webdriver
   driver = Selenium::WebDriver.for :firefox
   # :chrome -> chrome
   # :ie     -> iexplore
   

• Go to a specified URL

PureMath86

# import packages
from PIL import Image
import os
import argparse # build command-line interfaces


# construct the argument parse and parse the arguments
ap = argparse.ArgumentParser()
ap.add_argument("-d",
                "--directory",

PureMath86

# import the necessary packages
from PIL import Image # get image from disk in PIL format
import pytesseract # python "wrapper" of Google's Tesseract binaries
import argparse # build command-line interfaces
import cv2 # opencv-python
import os # operating system


# construct the argument parse and parse the arguments
ap = argparse.ArgumentParser()