135 lines
3.3 KiB
YAML
135 lines
3.3 KiB
YAML
Global:
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use_gpu: true
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epoch_num: 600
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log_smooth_window: 20
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print_batch_step: 10
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save_model_dir: ./output/det_mv3_pse/
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save_epoch_step: 600
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# evaluation is run every 63 iterations
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eval_batch_step: [ 0,63 ]
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cal_metric_during_train: False
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pretrained_model: ./pretrain_models/MobileNetV3_large_x0_5_pretrained
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checkpoints: #./output/det_r50_vd_pse_batch8_ColorJitter/best_accuracy
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save_inference_dir:
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use_visualdl: False
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infer_img: doc/imgs_en/img_10.jpg
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save_res_path: ./output/det_pse/predicts_pse.txt
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Architecture:
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model_type: det
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algorithm: PSE
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Transform: null
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Backbone:
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name: MobileNetV3
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scale: 0.5
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model_name: large
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Neck:
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name: FPN
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out_channels: 96
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Head:
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name: PSEHead
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hidden_dim: 96
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out_channels: 7
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Loss:
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name: PSELoss
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alpha: 0.7
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ohem_ratio: 3
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kernel_sample_mask: pred
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reduction: none
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Optimizer:
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name: Adam
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beta1: 0.9
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beta2: 0.999
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lr:
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name: Step
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learning_rate: 0.001
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step_size: 200
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gamma: 0.1
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regularizer:
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name: 'L2'
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factor: 0.0005
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PostProcess:
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name: PSEPostProcess
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thresh: 0
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box_thresh: 0.85
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min_area: 16
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box_type: box # 'box' or 'poly'
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scale: 1
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Metric:
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name: DetMetric
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main_indicator: hmean
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Train:
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dataset:
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name: SimpleDataSet
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data_dir: ./train_data/icdar2015/text_localization/
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label_file_list:
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- ./train_data/icdar2015/text_localization/train_icdar2015_label.txt
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ratio_list: [ 1.0 ]
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transforms:
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- DecodeImage: # load image
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img_mode: BGR
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channel_first: False
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- DetLabelEncode: # Class handling label
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- ColorJitter:
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brightness: 0.12549019607843137
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saturation: 0.5
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- IaaAugment:
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augmenter_args:
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- { 'type': Resize, 'args': { 'size': [ 0.5, 3 ] } }
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- { 'type': Fliplr, 'args': { 'p': 0.5 } }
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- { 'type': Affine, 'args': { 'rotate': [ -10, 10 ] } }
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- MakePseGt:
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kernel_num: 7
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min_shrink_ratio: 0.4
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size: 640
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- RandomCropImgMask:
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size: [ 640,640 ]
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main_key: gt_text
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crop_keys: [ 'image', 'gt_text', 'gt_kernels', 'mask' ]
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- NormalizeImage:
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scale: 1./255.
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mean: [ 0.485, 0.456, 0.406 ]
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std: [ 0.229, 0.224, 0.225 ]
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order: 'hwc'
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- ToCHWImage:
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- KeepKeys:
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keep_keys: [ 'image', 'gt_text', 'gt_kernels', 'mask' ] # the order of the dataloader list
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loader:
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shuffle: True
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drop_last: False
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batch_size_per_card: 16
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num_workers: 8
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Eval:
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dataset:
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name: SimpleDataSet
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data_dir: ./train_data/icdar2015/text_localization/
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label_file_list:
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- ./train_data/icdar2015/text_localization/test_icdar2015_label.txt
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ratio_list: [ 1.0 ]
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transforms:
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- DecodeImage: # load image
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img_mode: BGR
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channel_first: False
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- DetLabelEncode: # Class handling label
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- DetResizeForTest:
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limit_side_len: 736
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limit_type: min
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- NormalizeImage:
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scale: 1./255.
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mean: [ 0.485, 0.456, 0.406 ]
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std: [ 0.229, 0.224, 0.225 ]
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order: 'hwc'
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- ToCHWImage:
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- KeepKeys:
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keep_keys: [ 'image', 'shape', 'polys', 'ignore_tags' ]
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loader:
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shuffle: False
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drop_last: False
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batch_size_per_card: 1 # must be 1
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num_workers: 8 |