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- Global:
- use_gpu: true
- epoch_num: 100
- log_smooth_window: 20
- print_batch_step: 10
- save_model_dir: ./output/cls/mv3/
- save_epoch_step: 3
- # evaluation is run every 5000 iterations after the 4000th iteration
- eval_batch_step: [0, 1000]
- # if pretrained_model is saved in static mode, load_static_weights must set to True
- cal_metric_during_train: True
- pretrained_model:
- checkpoints:
- save_inference_dir:
- use_visualdl: False
- infer_img: doc/imgs_words_en/word_10.png
- label_list: ['0','180']
- Architecture:
- model_type: cls
- algorithm: CLS
- Transform:
- Backbone:
- name: MobileNetV3
- scale: 0.35
- model_name: small
- Neck:
- Head:
- name: ClsHead
- class_dim: 2
- Loss:
- name: ClsLoss
- Optimizer:
- name: Adam
- beta1: 0.9
- beta2: 0.999
- lr:
- name: Cosine
- learning_rate: 0.001
- regularizer:
- name: 'L2'
- factor: 0
- PostProcess:
- name: ClsPostProcess
- Metric:
- name: ClsMetric
- main_indicator: acc
- Train:
- dataset:
- name: SimpleDataSet
- data_dir: ./train_data/cls
- label_file_list:
- - ./train_data/cls/train.txt
- transforms:
- - DecodeImage: # load image
- img_mode: BGR
- channel_first: False
- - ClsLabelEncode: # Class handling label
- - RecAug:
- use_tia: False
- - RandAugment:
- - ClsResizeImg:
- image_shape: [3, 48, 192]
- - KeepKeys:
- keep_keys: ['image', 'label'] # dataloader will return list in this order
- loader:
- shuffle: True
- batch_size_per_card: 512
- drop_last: True
- num_workers: 8
- Eval:
- dataset:
- name: SimpleDataSet
- data_dir: ./train_data/cls
- label_file_list:
- - ./train_data/cls/test.txt
- transforms:
- - DecodeImage: # load image
- img_mode: BGR
- channel_first: False
- - ClsLabelEncode: # Class handling label
- - ClsResizeImg:
- image_shape: [3, 48, 192]
- - KeepKeys:
- keep_keys: ['image', 'label'] # dataloader will return list in this order
- loader:
- shuffle: False
- drop_last: False
- batch_size_per_card: 512
- num_workers: 4
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