2020-08-15 17:26:00 +08:00
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Global:
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algorithm: SAST
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use_gpu: true
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epoch_num: 2000
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log_smooth_window: 20
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print_batch_step: 2
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save_model_dir: ./output/det_sast/
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save_epoch_step: 20
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eval_batch_step: 5000
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train_batch_size_per_card: 8
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test_batch_size_per_card: 8
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image_shape: [3, 512, 512]
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reader_yml: ./configs/det/det_sast_icdar15_reader.yml
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pretrain_weights: ./pretrain_models/ResNet50_vd_ssld_pretrained/
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save_res_path: ./output/det_sast/predicts_sast.txt
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checkpoints:
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save_inference_dir:
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2020-11-05 17:47:21 +08:00
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infer_img:
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2020-08-15 17:26:00 +08:00
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Architecture:
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function: ppocr.modeling.architectures.det_model,DetModel
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Backbone:
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function: ppocr.modeling.backbones.det_resnet_vd_sast,ResNet
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layers: 50
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Head:
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function: ppocr.modeling.heads.det_sast_head,SASTHead
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model_name: large
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only_fpn_up: False
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# with_cab: False
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with_cab: True
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Loss:
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function: ppocr.modeling.losses.det_sast_loss,SASTLoss
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Optimizer:
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function: ppocr.optimizer,RMSProp
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base_lr: 0.001
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decay:
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function: piecewise_decay
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boundaries: [30000, 50000, 80000, 100000, 150000]
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decay_rate: 0.3
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PostProcess:
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function: ppocr.postprocess.sast_postprocess,SASTPostProcess
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score_thresh: 0.5
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sample_pts_num: 2
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nms_thresh: 0.2
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expand_scale: 1.0
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shrink_ratio_of_width: 0.3
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