rename output dir

configs/rec/rec_icdar15_train.yml

@@ -1,12 +1,12 @@
 Global:
   algorithm: CRNN
   use_gpu: true
-  epoch_num: 300
+  epoch_num: 3000
   log_smooth_window: 20
   print_batch_step: 10
-  save_model_dir: output_ic15
-  save_epoch_step: 3
-  eval_batch_step: 2000
+  save_model_dir: ./output/rec
+  save_epoch_step: 300
+  eval_batch_step: 500
   train_batch_size_per_card: 256
   test_batch_size_per_card: 256
   image_shape: [3, 32, 100]
@@ -37,6 +37,6 @@ Loss:
 
 Optimizer:
   function: ppocr.optimizer,AdamDecay
-  base_lr: 0.001
+  base_lr: 0.0001
   beta1: 0.9
   beta2: 0.999

ppocr/data/rec/dataset_traversal.py

@@ -184,6 +184,9 @@ class SimpleReader(object):
                     substr = label_infor.decode('utf-8').strip("\n").split("\t")
                     img_path = self.img_set_dir + "/" + substr[0]
                     img = cv2.imread(img_path)
+                    if img.shape[-1]==1 or len(list(img.shape))==2:
+                        print("this is a gry")
+                        img = cv2.cvtColor(img, cv2.COLOR_GRAY2BGR)
                     if img is None:
                         logger.info("{} does not exist!".format(img_path))
                         continue

ppocr/utils/character.py

@@ -64,7 +64,7 @@ class CharacterOps(object):
                     [sum(text_lengths)] = [text_index_0 + text_index_1 + ... + text_index_(n - 1)]
             length: length of each text. [batch_size]
         """
-        if self.character_type == "en":
+        if self.character_type == "en" or text.encode( 'UTF-8' ).isalpha():
             text = text.lower()
 
         text_list = []