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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,135 @@ | ||
| Global: | ||
| use_gpu: true | ||
| epoch_num: 600 | ||
| log_smooth_window: 20 | ||
| print_batch_step: 10 | ||
| save_model_dir: ./output/det_mv3_pse/ | ||
| save_epoch_step: 600 | ||
| # evaluation is run every 63 iterations | ||
| eval_batch_step: [ 0,63 ] | ||
| cal_metric_during_train: False | ||
| pretrained_model: ./pretrain_models/MobileNetV3_large_x0_5_pretrained | ||
| checkpoints: #./output/det_r50_vd_pse_batch8_ColorJitter/best_accuracy | ||
| save_inference_dir: | ||
| use_visualdl: False | ||
| infer_img: doc/imgs_en/img_10.jpg | ||
| save_res_path: ./output/det_pse/predicts_pse.txt | ||
|
|
||
| Architecture: | ||
| model_type: det | ||
| algorithm: PSE | ||
| Transform: null | ||
| Backbone: | ||
| name: MobileNetV3 | ||
| scale: 0.5 | ||
| model_name: large | ||
| Neck: | ||
| name: FPN | ||
| out_channels: 96 | ||
| Head: | ||
| name: PSEHead | ||
| hidden_dim: 96 | ||
| out_channels: 7 | ||
|
|
||
| Loss: | ||
| name: PSELoss | ||
| alpha: 0.7 | ||
| ohem_ratio: 3 | ||
| kernel_sample_mask: pred | ||
| reduction: none | ||
|
|
||
| Optimizer: | ||
| name: Adam | ||
| beta1: 0.9 | ||
| beta2: 0.999 | ||
| lr: | ||
| name: Step | ||
| learning_rate: 0.001 | ||
| step_size: 200 | ||
| gamma: 0.1 | ||
| regularizer: | ||
| name: 'L2' | ||
| factor: 0.0005 | ||
|
|
||
| PostProcess: | ||
| name: PSEPostProcess | ||
| thresh: 0 | ||
| box_thresh: 0.85 | ||
| min_area: 16 | ||
| box_type: box # 'box' or 'poly' | ||
| scale: 1 | ||
|
|
||
| Metric: | ||
| name: DetMetric | ||
| main_indicator: hmean | ||
|
|
||
| Train: | ||
| dataset: | ||
| name: SimpleDataSet | ||
| data_dir: ./train_data/icdar2015/text_localization/ | ||
| label_file_list: | ||
| - ./train_data/icdar2015/text_localization/train_icdar2015_label.txt | ||
| ratio_list: [ 1.0 ] | ||
| transforms: | ||
| - DecodeImage: # load image | ||
| img_mode: BGR | ||
| channel_first: False | ||
| - DetLabelEncode: # Class handling label | ||
| - ColorJitter: | ||
| brightness: 0.12549019607843137 | ||
| saturation: 0.5 | ||
| - IaaAugment: | ||
| augmenter_args: | ||
| - { 'type': Resize, 'args': { 'size': [ 0.5, 3 ] } } | ||
| - { 'type': Fliplr, 'args': { 'p': 0.5 } } | ||
| - { 'type': Affine, 'args': { 'rotate': [ -10, 10 ] } } | ||
| - MakePseGt: | ||
| kernel_num: 7 | ||
| min_shrink_ratio: 0.4 | ||
| size: 640 | ||
| - RandomCropImgMask: | ||
| size: [ 640,640 ] | ||
| main_key: gt_text | ||
| crop_keys: [ 'image', 'gt_text', 'gt_kernels', 'mask' ] | ||
| - 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', 'gt_text', 'gt_kernels', 'mask' ] # the order of the dataloader list | ||
| loader: | ||
| shuffle: True | ||
| drop_last: False | ||
| batch_size_per_card: 16 | ||
| num_workers: 8 | ||
|
|
||
| Eval: | ||
| dataset: | ||
| name: SimpleDataSet | ||
| data_dir: ./train_data/icdar2015/text_localization/ | ||
| label_file_list: | ||
| - ./train_data/icdar2015/text_localization/test_icdar2015_label.txt | ||
| ratio_list: [ 1.0 ] | ||
| transforms: | ||
| - DecodeImage: # load image | ||
| img_mode: BGR | ||
| channel_first: False | ||
| - DetLabelEncode: # Class handling label | ||
| - DetResizeForTest: | ||
| limit_side_len: 736 | ||
| limit_type: min | ||
| - 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 |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,134 @@ | ||
| Global: | ||
| use_gpu: true | ||
| epoch_num: 600 | ||
| log_smooth_window: 20 | ||
| print_batch_step: 10 | ||
| save_model_dir: ./output/det_r50_vd_pse/ | ||
| save_epoch_step: 600 | ||
| # evaluation is run every 125 iterations | ||
| eval_batch_step: [ 0,125 ] | ||
| cal_metric_during_train: False | ||
| pretrained_model: ./pretrain_models/ResNet50_vd_ssld_pretrained | ||
| checkpoints: #./output/det_r50_vd_pse_batch8_ColorJitter/best_accuracy | ||
| save_inference_dir: | ||
| use_visualdl: False | ||
| infer_img: doc/imgs_en/img_10.jpg | ||
| save_res_path: ./output/det_pse/predicts_pse.txt | ||
|
|
||
| Architecture: | ||
| model_type: det | ||
| algorithm: PSE | ||
| Transform: | ||
| Backbone: | ||
| name: ResNet | ||
| layers: 50 | ||
| Neck: | ||
| name: FPN | ||
| out_channels: 256 | ||
| Head: | ||
| name: PSEHead | ||
| hidden_dim: 256 | ||
| out_channels: 7 | ||
|
|
||
| Loss: | ||
| name: PSELoss | ||
| alpha: 0.7 | ||
| ohem_ratio: 3 | ||
| kernel_sample_mask: pred | ||
| reduction: none | ||
|
|
||
| Optimizer: | ||
| name: Adam | ||
| beta1: 0.9 | ||
| beta2: 0.999 | ||
| lr: | ||
| name: Step | ||
| learning_rate: 0.0001 | ||
| step_size: 200 | ||
| gamma: 0.1 | ||
| regularizer: | ||
| name: 'L2' | ||
| factor: 0.0005 | ||
|
|
||
| PostProcess: | ||
| name: PSEPostProcess | ||
| thresh: 0 | ||
| box_thresh: 0.85 | ||
| min_area: 16 | ||
| box_type: box # 'box' or 'poly' | ||
| scale: 1 | ||
|
|
||
| Metric: | ||
| name: DetMetric | ||
| main_indicator: hmean | ||
|
|
||
| Train: | ||
| dataset: | ||
| name: SimpleDataSet | ||
| data_dir: ./train_data/icdar2015/text_localization/ | ||
| label_file_list: | ||
| - ./train_data/icdar2015/text_localization/train_icdar2015_label.txt | ||
| ratio_list: [ 1.0 ] | ||
| transforms: | ||
| - DecodeImage: # load image | ||
| img_mode: BGR | ||
| channel_first: False | ||
| - DetLabelEncode: # Class handling label | ||
| - ColorJitter: | ||
| brightness: 0.12549019607843137 | ||
| saturation: 0.5 | ||
| - IaaAugment: | ||
| augmenter_args: | ||
| - { 'type': Resize, 'args': { 'size': [ 0.5, 3 ] } } | ||
| - { 'type': Fliplr, 'args': { 'p': 0.5 } } | ||
| - { 'type': Affine, 'args': { 'rotate': [ -10, 10 ] } } | ||
| - MakePseGt: | ||
| kernel_num: 7 | ||
| min_shrink_ratio: 0.4 | ||
| size: 640 | ||
| - RandomCropImgMask: | ||
| size: [ 640,640 ] | ||
| main_key: gt_text | ||
| crop_keys: [ 'image', 'gt_text', 'gt_kernels', 'mask' ] | ||
| - 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', 'gt_text', 'gt_kernels', 'mask' ] # the order of the dataloader list | ||
| loader: | ||
| shuffle: True | ||
| drop_last: False | ||
| batch_size_per_card: 8 | ||
| num_workers: 8 | ||
|
|
||
| Eval: | ||
| dataset: | ||
| name: SimpleDataSet | ||
| data_dir: ./train_data/icdar2015/text_localization/ | ||
| label_file_list: | ||
| - ./train_data/icdar2015/text_localization/test_icdar2015_label.txt | ||
| ratio_list: [ 1.0 ] | ||
| transforms: | ||
| - DecodeImage: # load image | ||
| img_mode: BGR | ||
| channel_first: False | ||
| - DetLabelEncode: # Class handling label | ||
| - DetResizeForTest: | ||
| limit_side_len: 736 | ||
| limit_type: min | ||
| - 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 |
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