modified label_ops

ppocr/data/imaug/label_ops.py

@@ -1248,19 +1248,4 @@ class SPINAttnLabelEncode(AttnLabelEncode):
 
         padded_text[:len(target)] = target
         data['label'] = np.array(padded_text)
-        return data
-
-    def get_ignored_tokens(self):
-        beg_idx = self.get_beg_end_flag_idx("beg")
-        end_idx = self.get_beg_end_flag_idx("end")
-        return [beg_idx, end_idx]
-
-    def get_beg_end_flag_idx(self, beg_or_end):
-        if beg_or_end == "beg":
-            idx = np.array(self.dict[self.beg_str])
-        elif beg_or_end == "end":
-            idx = np.array(self.dict[self.end_str])
-        else:
-            assert False, "Unsupport type %s in get_beg_end_flag_idx" \
-                          % beg_or_end
-        return 
\ No newline at end of file
+        return data 
\ No newline at end of file

ppocr/postprocess/rec_postprocess.py

@@ -668,86 +668,6 @@ class ABINetLabelDecode(NRTRLabelDecode):
         dict_character = ['</s>'] + dict_character
         return dict_character
 
-
-# class SPINAttnLabelDecode(BaseRecLabelDecode):
-#     """ Convert between text-label and text-index """
-
-#     def __init__(self, character_dict_path=None, use_space_char=False,
-#                  **kwargs):
-#         super(SPINAttnLabelDecode, self).__init__(character_dict_path,
-#                                               use_space_char)
-
-#     def add_special_char(self, dict_character):
-#         self.beg_str = "sos"
-#         self.end_str = "eos"
-#         dict_character = dict_character
-#         dict_character = [self.beg_str] + [self.end_str] + dict_character
-#         return dict_character
-
-#     def decode(self, text_index, text_prob=None, is_remove_duplicate=False):
-#         """ convert text-index into text-label. """
-#         result_list = []
-#         ignored_tokens = self.get_ignored_tokens()
-#         [beg_idx, end_idx] = self.get_ignored_tokens()
-#         batch_size = len(text_index)
-#         for batch_idx in range(batch_size):
-#             char_list = []
-#             conf_list = []
-#             for idx in range(len(text_index[batch_idx])):
-#                 if text_index[batch_idx][idx] == int(beg_idx):
-#                     continue
-#                 if int(text_index[batch_idx][idx]) == int(end_idx):
-#                     break
-#                 if is_remove_duplicate:
-#                     # only for predict
-#                     if idx > 0 and text_index[batch_idx][idx - 1] == text_index[
-#                             batch_idx][idx]:
-#                         continue
-#                 char_list.append(self.character[int(text_index[batch_idx][
-#                     idx])])
-#                 if text_prob is not None:
-#                     conf_list.append(text_prob[batch_idx][idx])
-#                 else:
-#                     conf_list.append(1)
-#             text = ''.join(char_list)
-#             result_list.append((text.lower(), np.mean(conf_list).tolist()))
-#         return result_list
-
-#     def __call__(self, preds, label=None, *args, **kwargs):
-#         """
-#         text = self.decode(text)
-#         if label is None:
-#             return text
-#         else:
-#             label = self.decode(label, is_remove_duplicate=False)
-#             return text, label
-#         """
-#         if isinstance(preds, paddle.Tensor):
-#             preds = preds.numpy()
-
-#         preds_idx = preds.argmax(axis=2)
-#         preds_prob = preds.max(axis=2)
-#         text = self.decode(preds_idx, preds_prob, is_remove_duplicate=False)
-#         if label is None:
-#             return text
-#         label = self.decode(label, is_remove_duplicate=False)
-#         return text, label
-
-#     def get_ignored_tokens(self):
-#         beg_idx = self.get_beg_end_flag_idx("beg")
-#         end_idx = self.get_beg_end_flag_idx("end")
-#         return [beg_idx, end_idx]
-
-#     def get_beg_end_flag_idx(self, beg_or_end):
-#         if beg_or_end == "beg":
-#             idx = np.array(self.dict[self.beg_str])
-#         elif beg_or_end == "end":
-#             idx = np.array(self.dict[self.end_str])
-#         else:
-#             assert False, "unsupport type %s in get_beg_end_flag_idx" \
-#                           % beg_or_end
-#         return idx
-
 class SPINAttnLabelDecode(AttnLabelDecode):
     """ Convert between text-label and text-index """