num_workers改为8

configs/det/det_mv3_db.yml

@@ -3,7 +3,7 @@ Global:
   epoch_num: 1200
   log_smooth_window: 20
   print_batch_step: 2
-  save_model_dir: ./output/20201010/
+  save_model_dir: ./output/db_mv3/
   save_epoch_step: 1200
   # evaluation is run every 5000 iterations after the 4000th iteration
   eval_batch_step: 8
@@ -66,9 +66,9 @@ Metric:
 TRAIN:
   dataset:
     name: SimpleDataSet
-    data_dir: /home/zhoujun20/detection/
+    data_dir: ./detection/
     file_list:
-      - /home/zhoujun20/detection/train_icdar2015_label.txt # dataset1
+      - ./detection/train_icdar2015_label.txt # dataset1
     ratio_list: [1.0]
     transforms:
       - DecodeImage: # load image
@@ -103,14 +103,14 @@ TRAIN:
     shuffle: True
     drop_last: False
     batch_size: 16
-    num_workers: 6
+    num_workers: 8
 
 EVAL:
   dataset:
     name: SimpleDataSet
-    data_dir: /home/zhoujun20/detection/
+    data_dir: ./detection/
     file_list:
-      - /home/zhoujun20/detection/test_icdar2015_label.txt
+      - ./detection/test_icdar2015_label.txt
     transforms:
       - DecodeImage: # load image
           img_mode: BGR
@@ -130,4 +130,4 @@ EVAL:
     shuffle: False
     drop_last: False
     batch_size: 1 # must be 1
-    num_workers: 6
\ No newline at end of file
+    num_workers: 8
\ No newline at end of file

configs/det/det_r50_vd_db.yml

@@ -3,14 +3,14 @@ Global:
   epoch_num: 1200
   log_smooth_window: 20
   print_batch_step: 2
-  save_model_dir: ./output/20201010/
+  save_model_dir: ./output/20201015_r50/
   save_epoch_step: 1200
   # evaluation is run every 5000 iterations after the 4000th iteration
   eval_batch_step: 8
   # if pretrained_model is saved in static mode, load_static_weights must set to True
   load_static_weights: True
   cal_metric_during_train: False
-  pretrained_model: /home/zhoujun20/pretrain_models/MobileNetV3_large_x0_5_pretrained
+  pretrained_model: /home/zhoujun20/pretrain_models/ResNet50_vd_ssld_pretrained/
   checkpoints: #./output/det_db_0.001_DiceLoss_256_pp_config_2.0b_4gpu/best_accuracy
   save_inference_dir:
   use_visualdl: True
@@ -102,7 +102,7 @@ TRAIN:
     shuffle: True
     drop_last: False
     batch_size: 16
-    num_workers: 6
+    num_workers: 8
 
 EVAL:
   dataset:
@@ -129,4 +129,4 @@ EVAL:
     shuffle: False
     drop_last: False
     batch_size: 1 # must be 1
-    num_workers: 6
\ No newline at end of file
+    num_workers: 8
\ No newline at end of file

configs/rec/rec_mv3_none_bilstm_ctc.yml

@@ -84,7 +84,7 @@ TRAIN:
     batch_size: 256
     shuffle: True
     drop_last: True
-    num_workers: 6
+    num_workers: 8
 
 EVAL:
   dataset:
@@ -105,4 +105,4 @@ EVAL:
     shuffle: False
     drop_last: False
     batch_size: 256
-    num_workers: 6
+    num_workers: 8

configs/rec/rec_mv3_none_bilstm_ctc_lmdb.yml

@@ -83,7 +83,7 @@ TRAIN:
     batch_size: 256
     shuffle: True
     drop_last: True
-    num_workers: 6
+    num_workers: 8
 
 EVAL:
   dataset:
@@ -103,4 +103,4 @@ EVAL:
     shuffle: False
     drop_last: False
     batch_size: 256
-    num_workers: 6
+    num_workers: 8

configs/rec/rec_mv3_none_none_ctc_lmdb.yml

+Global:
+  use_gpu: false
+  epoch_num: 500
+  log_smooth_window: 20
+  print_batch_step: 1
+  save_model_dir: ./output/rec/test/
+  save_epoch_step: 500
+  # evaluation is run every 5000 iterations after the 4000th iteration
+  eval_batch_step: 1016
+  # if pretrained_model is saved in static mode, load_static_weights must set to True
+  load_static_weights: True
+  cal_metric_during_train: True
+  pretrained_model:
+  checkpoints: #output/rec/rec_crnn/best_accuracy
+  save_inference_dir:
+  use_visualdl: True
+  infer_img: doc/imgs_words/ch/word_1.jpg
+  # for data or label process
+  max_text_length: 80
+  character_dict_path: /home/zhoujun20/rec/lmdb/dict.txt
+  character_type: 'en'
+  use_space_char: True
+  infer_mode: False
+  use_tps: False
+
+
+Optimizer:
+  name: Adam
+  beta1: 0.9
+  beta2: 0.999
+  learning_rate:
+    name: Cosine
+    lr: 0.0005
+    warmup_epoch: 1
+  regularizer:
+    name: 'L2'
+    factor: 0.00001
+
+Architecture:
+  type: rec
+  algorithm: CRNN
+  Transform:
+  Backbone:
+    name: MobileNetV3
+    scale: 0.5
+    model_name: small
+    small_stride: [ 1, 2, 2, 2 ]
+  Neck:
+    name: SequenceEncoder
+    encoder_type: reshape
+  Head:
+    name: CTC
+    fc_decay: 0.00001
+
+Loss:
+  name: CTCLoss
+
+PostProcess:
+  name: CTCLabelDecode
+
+Metric:
+  name: RecMetric
+  main_indicator: acc
+
+TRAIN:
+  dataset:
+    name: LMDBDateSet
+    file_list:
+      - /Users/zhoujun20/Downloads/evaluation_new # dataset1
+    ratio_list: [ 0.4,0.6 ]
+    transforms:
+      - DecodeImage: # load image
+          img_mode: BGR
+          channel_first: False
+      - CTCLabelEncode: # Class handling label
+      - RecAug:
+      - RecResizeImg:
+          image_shape: [ 3,32,320 ]
+      - keepKeys:
+          keep_keys: [ 'image','label','length' ] # dataloader将按照此顺序返回list
+  loader:
+    batch_size: 256
+    shuffle: True
+    drop_last: True
+    num_workers: 8
+
+EVAL:
+  dataset:
+    name: LMDBDateSet
+    file_list:
+      - /home/zhoujun20/rec/lmdb/val
+    transforms:
+      - DecodeImage: # load image
+          img_mode: BGR
+          channel_first: False
+      - CTCLabelEncode: # Class handling label
+      - RecResizeImg:
+          image_shape: [ 3,32,320 ]
+      - keepKeys:
+          keep_keys: [ 'image','label','length' ] # dataloader将按照此顺序返回list
+  loader:
+    shuffle: False
+    drop_last: False
+    batch_size: 256
+    num_workers: 8

configs/rec/rec_r34_vd_none_bilstm_ctc.yml

@@ -82,7 +82,7 @@ TRAIN:
     batch_size: 256
     shuffle: True
     drop_last: True
-    num_workers: 6
+    num_workers: 8
 
 EVAL:
   dataset:
@@ -103,4 +103,4 @@ EVAL:
     shuffle: False
     drop_last: False
     batch_size: 256
-    num_workers: 6
+    num_workers: 8