<jupyter_start><jupyter_text>Run Form Field HW Generation<jupyter_code># Run this
import os
import logging
import timeit

import numpy as np
import svgwrite

import drawing
import lyrics
from rnn import rnn

import random

import pandas as pd

from faker import Faker

from cairosvg import svg2png
import numpy as np
from PIL import Image
import pathlib as path

from form_field import *
from form_presets import *
from hw_image_generator import *
from customer_data_generators import *


# Modify Config File
from hw_generator_config import *<jupyter_output><empty_output><jupyter_text>Generate Customer Data<jupyter_code>tempdir = "temp_annotation"
if not os.path.exists(tempdir):
    os.mkdir(tempdir)
    
form_filler= FormFiller()
form_filler.generate_data(10)
form_filler.field_iterator(input_field_dict=FIELD_DICT,input_root=tempdir,input_df = form_filler.info_df)<jupyter_output><empty_output><jupyter_text>Generate Images with random position offset<jupyter_code>tempdir = "temp_annotation"
if not os.path.exists(tempdir):
    os.mkdir(tempdir)
    
form_filler= FormFiller()
form_filler.generate_data(10)
form_filler.field_iterator(input_field_dict=FIELD_DICT,input_root=tempdir,input_df = form_filler.info_df,
                               x_bias = int((random.random()-0.5) * 20),y_bias = int((random.random()-0.5) * 10))<jupyter_output><empty_output><jupyter_text>Generate 3-fields only10 handwriting styles<jupyter_code>tempdir = "temp_3fields"
if not os.path.exists(tempdir):
    os.mkdir(tempdir)
    
form_filler= FormFiller()
form_filler.generate_data(1000,in_positions=3)
form_filler.field_iterator(input_field_dict=FIELD_DICT_3FIELDS,
                           input_root=tempdir,input_df = form_filler.info_df,
                           x_bias = int((random.random()-0.5) * 20),
                           y_bias = int((random.random()-0.5) * 10))

tempdir = "temp_3fields_test"
if not os.path.exists(tempdir):
    os.mkdir(tempdir)
    
form_filler= FormFiller()
form_filler.generate_data(200,in_positions=3)
form_filler.field_iterator(input_field_dict=FIELD_DICT_3FIELDS,
                           input_root=tempdir,input_df = form_filler.info_df,
                           x_bias = int((random.random()-0.5) * 20),
                           y_bias = int((random.random()-0.5) * 10))<jupyter_output><empty_output><jupyter_text>Generate 7-fields only10 handwriting styles<jupyter_code>tempdir = "../data/temp_7fields"
if not os.path.exists(tempdir):
    os.mkdir(tempdir)
    
form_filler= FormFiller()
form_filler.generate_data(2000,in_positions=7)
form_filler.field_iterator(input_field_dict=FIELD_DICT_7FIELDS,
                           input_root=tempdir,input_df = form_filler.info_df,
                           x_bias = int((random.random()-0.5) * 20),
                           y_bias = int((random.random()-0.5) * 10))<jupyter_output><empty_output><jupyter_text>Generate SSN Fields<jupyter_code>tempdir = "../data/temp_ssn"
if not os.path.exists(tempdir):
    os.mkdir(tempdir)
    
form_filler= FormFiller()
form_filler.generate_data(20,in_positions=9)
form_filler.data_to_csv('tempssn.csv')
form_filler.set_handwriting()
form_filler.field_iterator(input_field_dict=FIELD_DICT_SSN,
                           input_root=tempdir,input_df = form_filler.info_df,
                           x_bias = int((random.random()-0.5) * 20),
                           y_bias = int((random.random()-0.5) * 10))<jupyter_output>INFO:tensorflow:Restoring parameters from checkpoints/model-17900<jupyter_text>Save Customer Info CSV<jupyter_code>form_filler.data_to_csv("metadata.csv")
!head metadata.csv<jupyter_output>uid,Name,BusinessName,Tax,Instructions,Exemptions,ExemptionCode,Address,City,Requester,Account,SocialSeciurityNumber,EmpIdentificationNumber
0,Mr. <NAME>,Chambers-Atkins,x,instructions ,exemptions  ,ex code ,Studio 73 Deborah views,Studio 76C King ford,Dr. <NAME>atherchester,- ,984-97-9056,ETJV08477069251619
1,<NAME>,Morgan LLC,x,instructions ,exemptions  ,ex code ,807 Margaret throughway,529 Brenda ville,<NAME>-Gray Clarkfurt,- ,952-74-9574,TWYB65922039531057<jupyter_text>Generate Form Annotation to CSV<jupyter_code>form_filler.generate_data(5,in_positions=True)
form_filler.data_to_csv("metadata_withloc.csv")
!head metadata_withloc.csv<jupyter_output>uid,Name,Name_loc,BusinessName,Tax,Instructions,Exemptions,ExemptionCode,Address,City,Requester,Account,SocialSeciurityNumber,EmpIdentificationNumber
0,<NAME>,"(190, 255)","<NAME>",x,instructions ,exemptions  ,ex code ,Flat 23a Jemma ranch,Studio 96 Barbara glens,Ms. Amelia Marsh South Bradleyside,- ,999-76-9604,GCAC91991907885988
1,<NAME>,"(190, 255)",Smith PLC,x,instructions ,exemptions  ,ex code ,Studio 72b Glen brook,Studio 40 Joel vista,<NAME> Lake Danny,- ,953-82-3576,GQIL48137712362849
2,<NAME>,"(190, 255)",Baker-Welch,x,instructions ,exemptions  ,ex code ,Flat 7 Whittaker drives,818 Smith glen,<NAME> Louisetown,- ,936-83-2479,TKNV57518129259177
3,<NAME>,"(190, 255)",Howell-Ahmed,x,instructions ,exemptions  ,ex code ,5 Mitchell drive,199 Olivia glens,<NAME>thonyville,- ,968-92-7898,GXRA94145495810863
4,<NAME>,"(190, 255)",Taylor Group,x,instructions ,exemptions  ,ex code ,Studio 71 Harding [...]
{'fraction_non_alphanumeric': 0.1124952088922959, 'fraction_numerical': 0.05423533921042545, 'mean_word_length': 4.985091743119266, 'pattern_counts': {'":': 0, '<': 43, '<?xml version=': 0, '>': 43, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '8', 'dir': 'jupyter-structured-clean-dedup', 'id': '479550', 'license': 'MIT', 'n_tokens_mistral': 2052, 'n_tokens_neox': 1849, 'n_words': 292, 'path': 'handwriting-synthesis/Run Generator.ipynb', 'repo_name': 'blow-the-fluff/parking', 'size': '5335'}