AssertionError: absence reader_yml in global

[zhenkunlin]

grep: warning: GREP_OPTIONS is deprecated; please use an alias or script Traceback (most recent call last): File "./tools/export_model.py", line 77, in main() File "./tools/export_model.py", line 49, in main startup_prog, evalprogram, place, config, = program.preprocess() File "/home/PaddleOCR/tools/program.py", line 654, in preprocess config = load_config(FLAGS.config) File "/home/PaddleOCR/tools/program.py", line 95, in load_config "absence reader_yml in global" AssertionError: absence reader_yml in global

[WenmuZhou]

看看你的配置文件里有没有reader_yml这个字段

[kano201]

我想使用develop分支将模型装换为model和param格式但是出现了同样的问题 下面是我的配置文件，用2.0和2.3版本都可以成功转换 Global: use_gpu: true epoch_num: 1200 log_smooth_window: 20 print_batch_step: 10 save_model_dir: ./output/db_mv3_block/ save_epoch_step: 1

evaluation is run every 2000 iterations

eval_batch_step: [0, 2000] cal_metric_during_train: False pretrained_model: ./output/db_mv3_block/best_accuracy checkpoints: save_inference_dir: use_visualdl: False infer_img: ../../data save_res_path: ./output/det_db/predicts_db.txt

Architecture: model_type: det algorithm: DB Transform: Backbone: name: MobileNetV3 scale: 0.5 model_name: large Neck: name: DBFPN out_channels: 256 Head: name: DBHead k: 50

Loss: name: DBLoss balance_loss: true main_loss_type: DiceLoss alpha: 5 beta: 10 ohem_ratio: 3

Optimizer: name: Adam beta1: 0.9 beta2: 0.999 lr: learning_rate: 0.001 regularizer: name: 'L2' factor: 0

PostProcess: name: DBPostProcess thresh: 0.3 box_thresh: 0.6 max_candidates: 1000 unclip_ratio: 1.5

Metric: name: DetMetric main_indicator: hmean

Train: dataset: name: SimpleDataSet data_dir: ../../ label_file_list:

• ../../train_label.txt ratio_list: [1.0] transforms:
• DecodeImage: # load image img_mode: BGR channel_first: False
• DetLabelEncode: # Class handling label
• IaaAugment: augmenter_args:
  • { 'type': Fliplr, 'args': { 'p': 0.5 } }
  • { 'type': Affine, 'args': { 'rotate': [-1, 1] } }
  • { 'type': Resize, 'args': { 'size': [0.5, 3] } }
• EastRandomCropData: size: [640, 640] max_tries: 50 keep_ratio: true
• MakeBorderMap: shrink_ratio: 0.4 thresh_min: 0.3 thresh_max: 0.7
• MakeShrinkMap: shrink_ratio: 0.4 min_text_size: 8
• NormalizeImage: scale: 1./255. mean: [0.485, 0.456, 0.406] std: [0.229, 0.224, 0.225] order: 'hwc'
• ToCHWImage:
• KeepKeys: keep_keys: ['image', 'threshold_map', 'threshold_mask', 'shrink_map', 'shrink_mask'] # the order of the dataloader list loader: shuffle: True drop_last: False batch_size_per_card: 8 num_workers: 8 use_shared_memory: False

Eval: dataset: name: SimpleDataSet data_dir: ../../ label_file_list:

• ../../test_label.txt transforms:
• DecodeImage: # load image img_mode: BGR channel_first: False
• DetLabelEncode: # Class handling label
• DetResizeForTest: image_shape: [736, 1280]
• NormalizeImage: scale: 1./255. mean: [0.485, 0.456, 0.406] std: [0.229, 0.224, 0.225] order: 'hwc'
• ToCHWImage:
• KeepKeys: keep_keys: ['image', 'shape', 'polys', 'ignore_tags'] loader: shuffle: False drop_last: False batch_size_per_card: 1 # must be 1 num_workers: 8 use_shared_memory: False

[paddle-bot-old[bot]]

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