# -*- coding: utf-8 -*-
# @Time : 2020/3/20 20:33
# @Author : zhoujun
"""
用于检查生成的json文件有没有问题
"""
from PIL import Image
from tqdm import tqdm
from matplotlib import pyplot as plt
from convert.utils import show_bbox_on_image, load_gt
if __name__ == '__main__':
json_path = r'D:\dataset\自然场景文字检测挑战赛初赛数据\验证集\validation_new.json'
data = load_gt(json_path)
for img_path, gt in tqdm(data.items()):
# print(gt['illegibility_list'])
# print(gt['texts'])
img = Image.open(img_path)
img = show_bbox_on_image(img, gt['polygons'], gt['texts'])
plt.imshow(img)
plt.show()
return item_dict['img']
if __name__ == '__main__':
from tqdm import tqdm
from torchvision import transforms
from matplotlib import pyplot as plt
# 支持中文
plt.rcParams['font.sans-serif'] = ['SimHei'] # 用来正常显示中文标签
plt.rcParams['axes.unicode_minus'] = False # 用来正常显示负号
json_path = r'D:\dataset\icdar2017rctw\detection\train.json'
dataset = DetDataSet(json_path, transform=transforms.ToTensor())
train_loader = DataLoader(dataset=dataset,
batch_size=1,
shuffle=True,
num_workers=0)
pbar = tqdm(total=len(train_loader))
for i, data in enumerate(train_loader):
img = data['img'][0].numpy().transpose(1, 2, 0) * 255
label = [x[0] for x in data['label']]
img = show_bbox_on_image(Image.fromarray(img.astype(np.uint8)),
data['polygons'], label)
plt.imshow(img)
plt.show()
pbar.update(1)
pbar.close()