creating_input.py

import pandas as pd
import numpy as np
import os
import sys
import tensorflow as tf
import cv2
from tqdm import tqdm
tqdm.pandas()
import urllib.request
import random
from PIL import Image
import matplotlib.pyplot as plt

def seed_everything(seed=51):
    random.seed(seed)
    os.environ['PYTHONHASHSEED'] = str(seed)
    np.random.seed(seed)
    tf.random.set_seed(seed)
seed_everything(seed=51)

target_data = np.load('data/target_data.npy')
target_data = list(target_data)

def get_words():
    word_url = "http://svnweb.freebsd.org/csrg/share/dict/words?view=co&content-type=text/plain"
    response = urllib.request.urlopen(word_url)
    long_txt = response.read().decode()
    words = long_txt.splitlines()
    return words

words = get_words()

print("Number of downloaded words : {}".format(len(words)) )
print(random.choice(words))
words = [x for x in words if len(x) < 8]
print("Number of short words: {}".format(len(words)) )
print(random.choice(words))

x_coors = list(range(0,128,1))
y_coors = list(range(32,256,1))
font_faces = [0,1,2,3,4,5,6,7,16]
font_scales = [1.5,2.0,2.5]
colors = [(0,0,0),(255,255,255)]
bolds = [1,2,3]

def create_input():
    input_data = []
    for img in tqdm(target_data):
        used_text = random.choice(words)
        x_coor = random.choice(x_coors)
        y_coor = random.choice(y_coors)
        font_face = random.choice(font_faces)
        font_scale = random.choice(font_scales)
        color = random.choice(colors)
        bold = random.choice(bolds)
        
        texted_image =cv2.putText(img=np.copy(img),
                                  text=used_text,
                                  org=(x_coor,y_coor),
                                  fontFace=font_face,
                                  fontScale=font_scale,
                                  color=color,
                                  thickness=bold)
        input_data.append(texted_image)
    np.save('data/input_data.npy', input_data)
    return input_data

input_data = create_input()

print(len(input_data))

if False:
    plt.imshow(input_data[0])