add sar dict

ppocr/losses/rec_sar_loss.py

@@ -9,11 +9,14 @@ from paddle import nn
 class SARLoss(nn.Layer):
     def __init__(self, **kwargs):
         super(SARLoss, self).__init__()
-        self.loss_func = paddle.nn.loss.CrossEntropyLoss(reduction="mean", ignore_index=96)
+        self.loss_func = paddle.nn.loss.CrossEntropyLoss(
+            reduction="mean", ignore_index=92)
 
     def forward(self, predicts, batch):
-        predict = predicts[:, :-1, :] # ignore last index of outputs to be in same seq_len with targets
-        label = batch[1].astype("int64")[:, 1:] # ignore first index of target in loss calculation
+        predict = predicts[:, :
+                           -1, :]  # ignore last index of outputs to be in same seq_len with targets
+        label = batch[1].astype(
+            "int64")[:, 1:]  # ignore first index of target in loss calculation
         batch_size, num_steps, num_classes = predict.shape[0], predict.shape[
             1], predict.shape[2]
         assert len(label.shape) == len(list(predict.shape)) - 1, \

ppocr/utils/dict90.txt

@@ -0,0 +1,90 @@
+0
+1
+2
+3
+4
+5
+6
+7
+8
+9
+a
+b
+c
+d
+e
+f
+g
+h
+i
+j
+k
+l
+m
+n
+o
+p
+q
+r
+s
+t
+u
+v
+w
+x
+y
+z
+A
+B
+C
+D
+E
+F
+G
+H
+I
+J
+K
+L
+M
+N
+O
+P
+Q
+R
+S
+T
+U
+V
+W
+X
+Y
+Z
+!
+"
+#
+$
+%
+&
+'
+(
+)
+*
++
+,
+-
+.
+/
+:
+;
+<
+=
+>
+?
+@
+[
+\
+]
+_
+`
+~