def test_icdar2015():
dataset = build_dataset('ICDAR2015', '../../data/icdar2015')
print(len(dataset))
average_time = []
for i in range(10):
tic = time.time()
data = dataset[i]
toc = time.time()
canvas = draw_polygons(data['image'], data['polygons'])
average_time.append(toc - tic)
plt.figure("img")
plt.figure(figsize=(12, 12))
plt.imshow(np.array(canvas, dtype=np.uint8))
plt.show()
print(np.mean(np.array(average_time)))
def build_train_data_loader(cfg):
names = cfg.DATA.NAMES
dirs = cfg.DATA.DIRS
dataset = []
for name, dataset_dir in zip(names, dirs):
dataset.append(build_dataset(name, dataset_dir))
# 读取数据集
dataset = ConcatDataset(dataset)
# 数据增强
dataset = Augment(dataset, cfg)
# encoder
dataset = TargetEncoder(dataset, cfg)
sampler = TrainingSampler(len(dataset))
data_loader = torch.utils.data.DataLoader(dataset,
cfg.SOLVER.BATCH_SIZE,
num_workers=cfg.SOLVER.NUM_WORKS,
pin_memory=cfg.SOLVER.PIN_MEMORY,
sampler=sampler)
return data_loader