利用已有的标注文字信息制作fake数据

from PIL import Image, ImageDraw, ImageFont, ImageFilter
import random
import glob
import numpy as np
import os
import cv2
from nespaper_semantics import seg_str'''
1. 从文字库随机选择10个字符
2. 生成图片
3. 随机使用函数
'''
# 从字库中随机选择n个字符
def sto_choice_from_info_str(info_str,quantity):start = random.randint(0, len(info_str)-(quantity+1))end = start + quantityrandom_word = info_str[start:end]return random_worddef random_word_color():font_color_choice = [[10, 10, 10], [5, 5, 5], [0, 0, 0]]font_color = random.choice(font_color_choice)noise = np.array([random.randint(0,2), random.randint(0,2), random.randint(0,2)])font_color = (np.array(font_color) + noise).tolist()return tuple(font_color)
# 生成一张背景图片
def create_an_image(bground_path, width, height):bground_list = os.listdir(bground_path)bground_choice = random.choice(bground_list)bground = cv2.imread(os.path.join(bground_path, bground_choice))x, y = random.randint(0, bground.shape[1]-width), random.randint(0, bground.shape[0]-height)bground = bground[y:y+height, x:x+width, :]return bground# 随机选取文字贴合起始的坐标, 根据背景的尺寸和字体的大小选择
def random_x_y(bground_size, font_size):height, width, _ = bground_sizeprint('bground_size:', bground_size)print('font_size:', font_size)# 为防止文字溢出图片，x，y要预留宽高# x = random.randint(0, width - font_size * 10)# y = random.randint(0, int((height-font_size)/4))"""====notice notice===="""#10个字要减140 9个字要减100 8个字要减80 7个字要减40 6个字要减20 5个字以下不用减x = random.randint(3, int((width - font_size) / 2))y = random.randint(10, height - font_size * 7)return x, ydef random_font_size():font_size = random.randint(22,25)return font_sizedef random_font(font_path):font_list = os.listdir(font_path)random_font = random.choice(font_list)return os.path.join(font_path, random_font)
def add_white_noise(image):rows, cols, dims = image.shaperandom_index=random.randint(10,100)for i in range(random_index):x = np.random.randint(2, rows)y = np.random.randint(2, cols)if random.getrandbits(1):image[x-1:x+1, y-1:y+1, :] = 180else:image[x, y, :] = 180return imagedef main(infostr, save_path, num,words_length,width,height,back_path,font_path):# 随机选取5个字符random_word_ori = sto_choice_from_info_str(infostr, words_length)print('random_word_ori:', random_word_ori)random_word = ''.join([i+'\n' for i in random_word_ori if i not in [':','(',')','｢','｣']])print('random_word:\n', random_word)# # 生成一张背景图片，已经剪裁好，宽高为280*32raw_image = create_an_image(back_path, width, height)# 随机选取字体大小font_size = random_font_size()# 随机选取字体font_name = random_font(font_path)print('font_name:', font_name)# 随机选取字体颜色font_color = random_word_color()# 随机选取文字贴合的起始坐标 x,ydraw_x, draw_y = random_x_y(raw_image.shape, font_size)# 将文本贴到背景图片raw_image = Image.fromarray(raw_image[..., ::-1])font = ImageFont.truetype(font_name, font_size)draw = ImageDraw.Draw(raw_image)draw.text((draw_x, draw_y), random_word, fill=font_color, font=font)raw_image = raw_image.rotate(0.3)image = add_white_noise(np.array(raw_image))# cv2.imwrite('image.jpg', image)# 保存文本信息和对应图片名称img_name = save_path+'/'+'fake_'+str(words_length)+'_'+str(num)+'.jpg'cv2.imwrite(img_name, image)with open(img_name.replace('.jpg','.txt'), 'w', encoding='utf-8') as file:[file.write(val) for val in random_word_ori]
def make_fake_data(total):#背景图片地址back_path = './background'#字体地址font_path = './font'#语料库 #从make_fake_word_library函数得到得到的语料库info_str = seg_strprint('len(info_str):', len(info_str))# 生成的字符个数words_length = 3output_path = 'data_set/fake_one_'+str(words_length)if not os.path.exists(output_path):os.mkdir(output_path)if words_length < 6:width=32height=200elif 6<=words_length<7:width = 32height = 220elif 7<=words_length<8:width = 32height = 240elif 8 <= words_length < 9:width = 32height = 280elif 9 <= words_length < 10:width = 32height = 300else:width = 32height = 340for i,num in enumerate(range(0, total)):if i<1:main(info_str, output_path, num, words_length, width, height,back_path,font_path)if num % 1000 == 0:print('[%d/%d]' % (num, total))
#根据标注的报纸制作语义库
def make_fake_word_library():import pandas as pdtrain_path = './label/train.txt'val_path = './label/val.txt'train_names = np.array(pd.read_csv(train_path, header=None))val_names = np.array(pd.read_csv(val_path, header=None))Semantics_list=[]for i,train_name in enumerate(train_names):words = train_name[0].split(' ')[-1]Semantics_list.append(words)for i,val_name in enumerate(val_names):words = val_name[0].split(' ')[-1]Semantics_list.append(words)print(len(Semantics_list))print(Semantics_list[:2])Semantics_str=''.join(Semantics_list)print(len(Semantics_str))print(Semantics_str)
if __name__ == '__main__':#用报纸制作的假数据make_fake_data(total=1000)# make_fake_word_library()

背景：