checkpoint_config = dict(interval=1) log_config = dict(interval=50, hooks=[dict(type="TextLoggerHook")]) dist_params = dict(backend="nccl") log_level = "INFO" load_from = None resume_from = "logs/satrn_big_2022-10-31/last.pth" workflow = [("train", 1)] opencv_num_threads = 0 mp_start_method = "fork" img_h = 32 img_w = 128 img_norm_cfg = dict(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]) train_pipeline = [ dict(type="LoadImageFromFile"), dict( type="ResizeOCR", height=32, min_width=128, max_width=128, keep_aspect_ratio=False, width_downsample_ratio=0.25, ), dict(type="ShearOCR", p=0.5, shear_limit=45), dict( type="ColorJitterOCR", p=0.5, brightness=0.25, contrast=0.25, saturation=0.25, hue=0.25, ), dict(type="GaussianNoiseOCR", p=0.5), dict(type="GaussianBlurOCR", blur=(3, 5), p=0.5), dict(type="BlackBoxAttackOCR", p=0.5, box_size=12), dict(type="DotAttackOCR", p=0.5, dot_size=(1, 3), dot_space=(5, 8)), dict(type="LineAttackOCR", p=0.5, line_size=(1, 3), line_space=(5, 8)), dict(type="InvertOCR", p=0.2), dict(type="ToTensorOCR"), dict(type="NormalizeOCR", mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]), dict( type="Collect", keys=["img"], meta_keys=[ "filename", "ori_shape", "img_shape", "text", "valid_ratio", "resize_shape", ], ), ] test_pipeline = [ dict(type="LoadImageFromFile"), dict( type="MultiRotateAugOCR", rotate_degrees=[0, 90, 270], transforms=[ dict( type="ResizeOCR", height=32, min_width=128, max_width=128, keep_aspect_ratio=False, width_downsample_ratio=0.25, ), dict(type="ToTensorOCR"), dict( type="NormalizeOCR", mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225], ), dict( type="Collect", keys=["img"], meta_keys=[ "filename", "ori_shape", "img_shape", "valid_ratio", "resize_shape", "img_norm_cfg", "ori_filename", ], ), ], ), ] dataset_type = "OCRDataset" img_path_prefix = "data/Recognition/Real/" dataset_list = "data/AnnFiles/current-dirs/2022-10-19/" default_loader = dict( type="AnnFileLoader", repeat=1, parser=dict( type="LineStrParser", keys=["filename", "text"], keys_idx=[0, 1], separator=" " ), ) default_dataset = dict( type="OCRDataset", img_prefix=None, ann_file=None, loader=dict( type="AnnFileLoader", repeat=1, parser=dict( type="LineStrParser", keys=["filename", "text"], keys_idx=[0, 1], separator=" ", ), ), pipeline=None, test_mode=False, ) handwriten_train = dict( type="OCRDataset", img_prefix=("data/Recognition/Real/Train/Handwritten_Train/",), ann_file="data/AnnFiles/current-dirs/2022-10-19/text_recognition__Train_Handwritten_Train.txt", loader=dict( type="AnnFileLoader", repeat=1, parser=dict( type="LineStrParser", keys=["filename", "text"], keys_idx=[0, 1], separator=" ", ), ), pipeline=None, test_mode=False, ) printed_train = dict( type="OCRDataset", img_prefix=("data/Recognition/Real/Train/Printed_Train/",), ann_file=( "data/AnnFiles/current-dirs/2022-10-19/text_recognition__Train_Printed_Train.txt", ), loader=dict( type="AnnFileLoader", repeat=1, parser=dict( type="LineStrParser", keys=["filename", "text"], keys_idx=[0, 1], separator=" ", ), ), pipeline=None, test_mode=False, ) handwriten_val = dict( type="OCRDataset", img_prefix=("data/Recognition/Real/Val/Handwritten_Val/",), ann_file=( "data/AnnFiles/current-dirs/2022-10-19/text_recognition__Val_Handwritten_Val.txt", ), loader=dict( type="AnnFileLoader", repeat=1, parser=dict( type="LineStrParser", keys=["filename", "text"], keys_idx=[0, 1], separator=" ", ), ), pipeline=None, test_mode=False, ) printed_val = dict( type="OCRDataset", img_prefix=("data/Recognition/Real/Val/Printed_Val/",), ann_file=( "data/AnnFiles/current-dirs/2022-10-19/text_recognition__Val_Printed_Val.txt", ), loader=dict( type="AnnFileLoader", repeat=1, parser=dict( type="LineStrParser", keys=["filename", "text"], keys_idx=[0, 1], separator=" ", ), ), pipeline=None, test_mode=False, ) synthetic = dict( type="OCRDataset", img_prefix=("data/Recognition/Synthetic/Using/",), ann_file=( "data/AnnFiles/current-dirs/2022-10-19/text_recognition_Synthetic_Using.txt", ), loader=dict( type="AnnFileLoader", repeat=1, parser=dict( type="LineStrParser", keys=["filename", "text"], keys_idx=[0, 1], separator=" ", ), ), pipeline=None, test_mode=False, ) blank_space = dict( type="OCRDataset", img_prefix=("data/Recognition/Blank/Train/",), ann_file=( "data/AnnFiles/current-dirs/2022-10-19/text_recognition_Blank_Train.txt", ), loader=dict( type="AnnFileLoader", repeat=1, parser=dict( type="LineStrParser", keys=["filename", "text"], keys_idx=[0, 1], separator=" ", ), ), pipeline=None, test_mode=False, ) captcha_train = dict( type="OCRDataset", img_prefix=("data/Recognition/Real/Train/Captcha_Train/DONE/",), ann_file=( "data/AnnFiles/current-dirs/2022-10-19/text_recognition_Captcha_Train_DONE.txt", ), loader=dict( type="AnnFileLoader", repeat=1, parser=dict( type="LineStrParser", keys=["filename", "text"], keys_idx=[0, 1], separator=" ", ), ), pipeline=None, test_mode=False, ) captcha_val = dict( type="OCRDataset", img_prefix=("data/Recognition/Real/Val/Captcha_Val/DONE/",), ann_file=( "data/AnnFiles/current-dirs/2022-10-19/text_recognition_Captcha_Val_DONE.txt", ), loader=dict( type="AnnFileLoader", repeat=1, parser=dict( type="LineStrParser", keys=["filename", "text"], keys_idx=[0, 1], separator=" ", ), ), pipeline=None, test_mode=False, ) kie_train = dict( type="OCRDataset", img_prefix=("data/Recognition/Real/Train/KIE_Train/KIE/",), ann_file=( "data/AnnFiles/current-dirs/2022-10-19/text_recognition_KIE_Train_KIE.txt", ), loader=dict( type="AnnFileLoader", repeat=1, parser=dict( type="LineStrParser", keys=["filename", "text"], keys_idx=[0, 1], separator=" ", ), ), pipeline=None, test_mode=False, ) kie_val = dict( type="OCRDataset", img_prefix=("data/Recognition/Real/Val/KIE_Val/KIE/",), ann_file=( "data/AnnFiles/current-dirs/2022-10-19/text_recognition_KIE_Val_KIE.txt", ), loader=dict( type="AnnFileLoader", repeat=1, parser=dict( type="LineStrParser", keys=["filename", "text"], keys_idx=[0, 1], separator=" ", ), ), pipeline=None, test_mode=False, ) gplx_train = dict( type="OCRDataset", img_prefix=("data/Recognition/Real/Train/GPLX_Train/train/",), ann_file=( "data/AnnFiles/current-dirs/2022-10-19/text_recognition_GPLX_Train_train.txt", ), loader=dict( type="AnnFileLoader", repeat=1, parser=dict( type="LineStrParser", keys=["filename", "text"], keys_idx=[0, 1], separator=" ", ), ), pipeline=None, test_mode=False, ) gplx_val = dict( type="OCRDataset", img_prefix=("data/Recognition/Real/Val/GPLX_Val/val/",), ann_file=( "data/AnnFiles/current-dirs/2022-10-19/text_recognition_GPLX_Val_val.txt", ), loader=dict( type="AnnFileLoader", repeat=1, parser=dict( type="LineStrParser", keys=["filename", "text"], keys_idx=[0, 1], separator=" ", ), ), pipeline=None, test_mode=False, ) vietocr = dict( type="OCRDataset", img_prefix=("data/Recognition/Real/Train/VietOCR_Train/Data/",), ann_file=( "data/AnnFiles/current-dirs/2022-10-19/text_recognition_VietOCR_Train_Data.txt", ), loader=dict( type="AnnFileLoader", repeat=1, parser=dict( type="LineStrParser", keys=["filename", "text"], keys_idx=[0, 1], separator=" ", ), ), pipeline=None, test_mode=False, ) train_list = [ dict( type="OCRDataset", img_prefix=("data/Recognition/Real/Train/Handwritten_Train/",), ann_file="data/AnnFiles/current-dirs/2022-10-19/text_recognition__Train_Handwritten_Train.txt", loader=dict( type="AnnFileLoader", repeat=1, parser=dict( type="LineStrParser", keys=["filename", "text"], keys_idx=[0, 1], separator=" ", ), ), pipeline=None, test_mode=False, ), dict( type="OCRDataset", img_prefix=("data/Recognition/Real/Train/Printed_Train/",), ann_file=( "data/AnnFiles/current-dirs/2022-10-19/text_recognition__Train_Printed_Train.txt", ), loader=dict( type="AnnFileLoader", repeat=1, parser=dict( type="LineStrParser", keys=["filename", "text"], keys_idx=[0, 1], separator=" ", ), ), pipeline=None, test_mode=False, ), dict( type="OCRDataset", img_prefix=("data/Recognition/Synthetic/Using/",), ann_file=( "data/AnnFiles/current-dirs/2022-10-19/text_recognition_Synthetic_Using.txt", ), loader=dict( type="AnnFileLoader", repeat=1, parser=dict( type="LineStrParser", keys=["filename", "text"], keys_idx=[0, 1], separator=" ", ), ), pipeline=None, test_mode=False, ), dict( type="OCRDataset", img_prefix=("data/Recognition/Blank/Train/",), ann_file=( "data/AnnFiles/current-dirs/2022-10-19/text_recognition_Blank_Train.txt", ), loader=dict( type="AnnFileLoader", repeat=1, parser=dict( type="LineStrParser", keys=["filename", "text"], keys_idx=[0, 1], separator=" ", ), ), pipeline=None, test_mode=False, ), dict( type="OCRDataset", img_prefix=("data/Recognition/Real/Train/Captcha_Train/DONE/",), ann_file=( "data/AnnFiles/current-dirs/2022-10-19/text_recognition_Captcha_Train_DONE.txt", ), loader=dict( type="AnnFileLoader", repeat=1, parser=dict( type="LineStrParser", keys=["filename", "text"], keys_idx=[0, 1], separator=" ", ), ), pipeline=None, test_mode=False, ), dict( type="OCRDataset", img_prefix=("data/Recognition/Real/Train/KIE_Train/KIE/",), ann_file=( "data/AnnFiles/current-dirs/2022-10-19/text_recognition_KIE_Train_KIE.txt", ), loader=dict( type="AnnFileLoader", repeat=1, parser=dict( type="LineStrParser", keys=["filename", "text"], keys_idx=[0, 1], separator=" ", ), ), pipeline=None, test_mode=False, ), dict( type="OCRDataset", img_prefix=("data/Recognition/Real/Train/GPLX_Train/train/",), ann_file=( "data/AnnFiles/current-dirs/2022-10-19/text_recognition_GPLX_Train_train.txt", ), loader=dict( type="AnnFileLoader", repeat=1, parser=dict( type="LineStrParser", keys=["filename", "text"], keys_idx=[0, 1], separator=" ", ), ), pipeline=None, test_mode=False, ), dict( type="OCRDataset", img_prefix=("data/Recognition/Real/Train/VietOCR_Train/Data/",), ann_file=( "data/AnnFiles/current-dirs/2022-10-19/text_recognition_VietOCR_Train_Data.txt", ), loader=dict( type="AnnFileLoader", repeat=1, parser=dict( type="LineStrParser", keys=["filename", "text"], keys_idx=[0, 1], separator=" ", ), ), pipeline=None, test_mode=False, ), ] val_list = [ dict( type="OCRDataset", img_prefix=("data/Recognition/Real/Val/Handwritten_Val/",), ann_file=( "data/AnnFiles/current-dirs/2022-10-19/text_recognition__Val_Handwritten_Val.txt", ), loader=dict( type="AnnFileLoader", repeat=1, parser=dict( type="LineStrParser", keys=["filename", "text"], keys_idx=[0, 1], separator=" ", ), ), pipeline=None, test_mode=False, ), dict( type="OCRDataset", img_prefix=("data/Recognition/Real/Val/Printed_Val/",), ann_file=( "data/AnnFiles/current-dirs/2022-10-19/text_recognition__Val_Printed_Val.txt", ), loader=dict( type="AnnFileLoader", repeat=1, parser=dict( type="LineStrParser", keys=["filename", "text"], keys_idx=[0, 1], separator=" ", ), ), pipeline=None, test_mode=False, ), dict( type="OCRDataset", img_prefix=("data/Recognition/Real/Val/Captcha_Val/DONE/",), ann_file=( "data/AnnFiles/current-dirs/2022-10-19/text_recognition_Captcha_Val_DONE.txt", ), loader=dict( type="AnnFileLoader", repeat=1, parser=dict( type="LineStrParser", keys=["filename", "text"], keys_idx=[0, 1], separator=" ", ), ), pipeline=None, test_mode=False, ), dict( type="OCRDataset", img_prefix=("data/Recognition/Real/Val/KIE_Val/KIE/",), ann_file=( "data/AnnFiles/current-dirs/2022-10-19/text_recognition_KIE_Val_KIE.txt", ), loader=dict( type="AnnFileLoader", repeat=1, parser=dict( type="LineStrParser", keys=["filename", "text"], keys_idx=[0, 1], separator=" ", ), ), pipeline=None, test_mode=False, ), dict( type="OCRDataset", img_prefix=("data/Recognition/Real/Val/GPLX_Val/val/",), ann_file=( "data/AnnFiles/current-dirs/2022-10-19/text_recognition_GPLX_Val_val.txt", ), loader=dict( type="AnnFileLoader", repeat=1, parser=dict( type="LineStrParser", keys=["filename", "text"], keys_idx=[0, 1], separator=" ", ), ), pipeline=None, test_mode=False, ), ] test_list = [ dict( type="OCRDataset", img_prefix=("data/Recognition/Real/Val/Handwritten_Val/",), ann_file=( "data/AnnFiles/current-dirs/2022-10-19/text_recognition__Val_Handwritten_Val.txt", ), loader=dict( type="AnnFileLoader", repeat=1, parser=dict( type="LineStrParser", keys=["filename", "text"], keys_idx=[0, 1], separator=" ", ), ), pipeline=None, test_mode=False, ), dict( type="OCRDataset", img_prefix=("data/Recognition/Real/Val/Printed_Val/",), ann_file=( "data/AnnFiles/current-dirs/2022-10-19/text_recognition__Val_Printed_Val.txt", ), loader=dict( type="AnnFileLoader", repeat=1, parser=dict( type="LineStrParser", keys=["filename", "text"], keys_idx=[0, 1], separator=" ", ), ), pipeline=None, test_mode=False, ), ] fp16 = dict(loss_scale="dynamic") label_convertor = dict(type="AttnConvertor", dict_type="DICT224", with_unknown=False) model = dict( type="SATRN", backbone=dict(type="ResNetABI", in_channels=3, stem_channels=16, base_channels=16), encoder=dict( type="SatrnEncoder", n_layers=12, n_head=8, d_k=32, d_v=32, d_model=256, n_position=100, d_inner=1024, dropout=0.1, ), decoder=dict( type="NRTRDecoder", n_layers=12, d_embedding=256, n_head=8, d_model=256, d_inner=1024, d_k=32, d_v=32, ), loss=dict(type="TFLoss"), label_convertor=dict(type="AttnConvertor", dict_type="DICT224", with_unknown=False), max_seq_len=25, ) optimizer = dict(type="Adam", lr=0.001) optimizer_config = dict(grad_clip=None) lr_config = dict(policy="poly", power=0.9, min_lr=1e-06, by_epoch=False) total_epochs = 15 custom_hooks = [ dict( type="ExpMomentumEMAHook", total_iter=20000, resume_from=None, momentum=0.0001, priority=49, ) ] data = dict( samples_per_gpu=160, workers_per_gpu=16, val_dataloader=dict(samples_per_gpu=400), test_dataloader=dict(samples_per_gpu=400), train=dict( type="UniformConcatDataset", datasets=[ dict( type="OCRDataset", img_prefix=("data/Recognition/Real/Train/Handwritten_Train/",), ann_file="data/AnnFiles/current-dirs/2022-10-19/text_recognition__Train_Handwritten_Train.txt", loader=dict( type="AnnFileLoader", repeat=1, parser=dict( type="LineStrParser", keys=["filename", "text"], keys_idx=[0, 1], separator=" ", ), ), pipeline=None, test_mode=False, ), dict( type="OCRDataset", img_prefix=("data/Recognition/Real/Train/Printed_Train/",), ann_file=( "data/AnnFiles/current-dirs/2022-10-19/text_recognition__Train_Printed_Train.txt", ), loader=dict( type="AnnFileLoader", repeat=1, parser=dict( type="LineStrParser", keys=["filename", "text"], keys_idx=[0, 1], separator=" ", ), ), pipeline=None, test_mode=False, ), dict( type="OCRDataset", img_prefix=("data/Recognition/Synthetic/Using/",), ann_file=( "data/AnnFiles/current-dirs/2022-10-19/text_recognition_Synthetic_Using.txt", ), loader=dict( type="AnnFileLoader", repeat=1, parser=dict( type="LineStrParser", keys=["filename", "text"], keys_idx=[0, 1], separator=" ", ), ), pipeline=None, test_mode=False, ), dict( type="OCRDataset", img_prefix=("data/Recognition/Blank/Train/",), ann_file=( "data/AnnFiles/current-dirs/2022-10-19/text_recognition_Blank_Train.txt", ), loader=dict( type="AnnFileLoader", repeat=1, parser=dict( type="LineStrParser", keys=["filename", "text"], keys_idx=[0, 1], separator=" ", ), ), pipeline=None, test_mode=False, ), dict( type="OCRDataset", img_prefix=("data/Recognition/Real/Train/Captcha_Train/DONE/",), ann_file=( "data/AnnFiles/current-dirs/2022-10-19/text_recognition_Captcha_Train_DONE.txt", ), loader=dict( type="AnnFileLoader", repeat=1, parser=dict( type="LineStrParser", keys=["filename", "text"], keys_idx=[0, 1], separator=" ", ), ), pipeline=None, test_mode=False, ), dict( type="OCRDataset", img_prefix=("data/Recognition/Real/Train/KIE_Train/KIE/",), ann_file=( "data/AnnFiles/current-dirs/2022-10-19/text_recognition_KIE_Train_KIE.txt", ), loader=dict( type="AnnFileLoader", repeat=1, parser=dict( type="LineStrParser", keys=["filename", "text"], keys_idx=[0, 1], separator=" ", ), ), pipeline=None, test_mode=False, ), dict( type="OCRDataset", img_prefix=("data/Recognition/Real/Train/GPLX_Train/train/",), ann_file=( "data/AnnFiles/current-dirs/2022-10-19/text_recognition_GPLX_Train_train.txt", ), loader=dict( type="AnnFileLoader", repeat=1, parser=dict( type="LineStrParser", keys=["filename", "text"], keys_idx=[0, 1], separator=" ", ), ), pipeline=None, test_mode=False, ), dict( type="OCRDataset", img_prefix=("data/Recognition/Real/Train/VietOCR_Train/Data/",), ann_file=( "data/AnnFiles/current-dirs/2022-10-19/text_recognition_VietOCR_Train_Data.txt", ), loader=dict( type="AnnFileLoader", repeat=1, parser=dict( type="LineStrParser", keys=["filename", "text"], keys_idx=[0, 1], separator=" ", ), ), pipeline=None, test_mode=False, ), ], pipeline=[ dict(type="LoadImageFromFile"), dict( type="ResizeOCR", height=32, min_width=128, max_width=128, keep_aspect_ratio=False, width_downsample_ratio=0.25, ), dict(type="ShearOCR", p=0.5, shear_limit=45), dict( type="ColorJitterOCR", p=0.5, brightness=0.25, contrast=0.25, saturation=0.25, hue=0.25, ), dict(type="GaussianNoiseOCR", p=0.5), dict(type="GaussianBlurOCR", blur=(3, 5), p=0.5), dict(type="BlackBoxAttackOCR", p=0.5, box_size=12), dict(type="DotAttackOCR", p=0.5, dot_size=(1, 3), dot_space=(5, 8)), dict(type="LineAttackOCR", p=0.5, line_size=(1, 3), line_space=(5, 8)), dict(type="InvertOCR", p=0.2), dict(type="ToTensorOCR"), dict( type="NormalizeOCR", mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225], ), dict( type="Collect", keys=["img"], meta_keys=[ "filename", "ori_shape", "img_shape", "text", "valid_ratio", "resize_shape", ], ), ], ), val=dict( type="UniformConcatDataset", datasets=[ dict( type="OCRDataset", img_prefix=("data/Recognition/Real/Val/Handwritten_Val/",), ann_file=( "data/AnnFiles/current-dirs/2022-10-19/text_recognition__Val_Handwritten_Val.txt", ), loader=dict( type="AnnFileLoader", repeat=1, parser=dict( type="LineStrParser", keys=["filename", "text"], keys_idx=[0, 1], separator=" ", ), ), pipeline=None, test_mode=False, ), dict( type="OCRDataset", img_prefix=("data/Recognition/Real/Val/Printed_Val/",), ann_file=( "data/AnnFiles/current-dirs/2022-10-19/text_recognition__Val_Printed_Val.txt", ), loader=dict( type="AnnFileLoader", repeat=1, parser=dict( type="LineStrParser", keys=["filename", "text"], keys_idx=[0, 1], separator=" ", ), ), pipeline=None, test_mode=False, ), dict( type="OCRDataset", img_prefix=("data/Recognition/Real/Val/Captcha_Val/DONE/",), ann_file=( "data/AnnFiles/current-dirs/2022-10-19/text_recognition_Captcha_Val_DONE.txt", ), loader=dict( type="AnnFileLoader", repeat=1, parser=dict( type="LineStrParser", keys=["filename", "text"], keys_idx=[0, 1], separator=" ", ), ), pipeline=None, test_mode=False, ), dict( type="OCRDataset", img_prefix=("data/Recognition/Real/Val/KIE_Val/KIE/",), ann_file=( "data/AnnFiles/current-dirs/2022-10-19/text_recognition_KIE_Val_KIE.txt", ), loader=dict( type="AnnFileLoader", repeat=1, parser=dict( type="LineStrParser", keys=["filename", "text"], keys_idx=[0, 1], separator=" ", ), ), pipeline=None, test_mode=False, ), dict( type="OCRDataset", img_prefix=("data/Recognition/Real/Val/GPLX_Val/val/",), ann_file=( "data/AnnFiles/current-dirs/2022-10-19/text_recognition_GPLX_Val_val.txt", ), loader=dict( type="AnnFileLoader", repeat=1, parser=dict( type="LineStrParser", keys=["filename", "text"], keys_idx=[0, 1], separator=" ", ), ), pipeline=None, test_mode=False, ), ], pipeline=[ dict(type="LoadImageFromFile"), dict( type="MultiRotateAugOCR", rotate_degrees=[0, 90, 270], transforms=[ dict( type="ResizeOCR", height=32, min_width=128, max_width=128, keep_aspect_ratio=False, width_downsample_ratio=0.25, ), dict(type="ToTensorOCR"), dict( type="NormalizeOCR", mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225], ), dict( type="Collect", keys=["img"], meta_keys=[ "filename", "ori_shape", "img_shape", "valid_ratio", "resize_shape", "img_norm_cfg", "ori_filename", ], ), ], ), ], ), test=dict( type="UniformConcatDataset", datasets=[ dict( type="OCRDataset", img_prefix=("data/Recognition/Real/Val/Handwritten_Val/",), ann_file=( "data/AnnFiles/current-dirs/2022-10-19/text_recognition__Val_Handwritten_Val.txt", ), loader=dict( type="AnnFileLoader", repeat=1, parser=dict( type="LineStrParser", keys=["filename", "text"], keys_idx=[0, 1], separator=" ", ), ), pipeline=None, test_mode=False, ), dict( type="OCRDataset", img_prefix=("data/Recognition/Real/Val/Printed_Val/",), ann_file=( "data/AnnFiles/current-dirs/2022-10-19/text_recognition__Val_Printed_Val.txt", ), loader=dict( type="AnnFileLoader", repeat=1, parser=dict( type="LineStrParser", keys=["filename", "text"], keys_idx=[0, 1], separator=" ", ), ), pipeline=None, test_mode=False, ), ], pipeline=[ dict(type="LoadImageFromFile"), dict( type="MultiRotateAugOCR", rotate_degrees=[0, 90, 270], transforms=[ dict( type="ResizeOCR", height=32, min_width=128, max_width=128, keep_aspect_ratio=False, width_downsample_ratio=0.25, ), dict(type="ToTensorOCR"), dict( type="NormalizeOCR", mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225], ), dict( type="Collect", keys=["img"], meta_keys=[ "filename", "ori_shape", "img_shape", "valid_ratio", "resize_shape", "img_norm_cfg", "ori_filename", ], ), ], ), ], ), ) evaluation = dict(interval=1, metric="acc") work_dir = "logs/satrn_big_2022-10-31/" gpu_ids = [0]