Merge pull request #6254 from LDOUBLEV/dygraph

[doc] add r50 base

doc/doc_ch/PP-OCRv3_introduction.md

@@ -53,11 +53,10 @@ PP-OCRv3检测模型是对PP-OCRv2中的[CML](https://arxiv.org/pdf/2109.03144.p
 
 |序号|策略|模型大小|hmean|速度（cpu + mkldnn)|
 |-|-|-|-|-|
-|baseline teacher|PP-OCR server|49M|83.2%|171ms|
+|baseline teacher|DB-R50|99M|83.5%|260ms|
 |teacher1|DB-R50-LK-PAN|124M|85.0%|396ms|
 |teacher2|DB-R50-LK-PAN-DML|124M|86.0%|396ms|
 |baseline student|PP-OCRv2|3M|83.2%|117ms|
-|student0|DB-MV3-RSE-FPN|3.6M|84.5%|124ms|
 |student1|DB-MV3-CML（teacher2）|3M|84.3%|117ms|
 |student2|DB-MV3-RSE-FPN-CML（teacher2）|3.6M|85.4%|124ms|
 

doc/doc_en/PP-OCRv3_introduction_en.md

@@ -55,11 +55,10 @@ The ablation experiments are as follows:
 
 |ID|Strategy|Model Size|Hmean|The Inference Time（cpu + mkldnn)|
 |-|-|-|-|-|
-|baseline teacher|PP-OCR server|49M|83.2%|171ms|
+|baseline teacher|DB-R50|99M|83.5%|260ms|
 |teacher1|DB-R50-LK-PAN|124M|85.0%|396ms|
 |teacher2|DB-R50-LK-PAN-DML|124M|86.0%|396ms|
 |baseline student|PP-OCRv2|3M|83.2%|117ms|
-|student0|DB-MV3-RSE-FPN|3.6M|84.5%|124ms|
 |student1|DB-MV3-CML（teacher2）|3M|84.3%|117ms|
 |student2|DB-MV3-RSE-FPN-CML（teacher2）|3.6M|85.4%|124ms|
 

ppocr/data/imaug/label_ops.py

@@ -438,7 +438,12 @@ class KieLabelEncode(object):
             texts.append(ann['transcription'])
             text_ind = [self.dict[c] for c in text if c in self.dict]
             text_inds.append(text_ind)
-            labels.append(ann['label'])
+            if 'label' in anno.keys():
+                labels.append(ann['label'])
+            elif 'key_cls' in anno.keys():
+                labels.append(anno['key_cls'])
+            else:
+                raise ValueError("Cannot found 'key_cls' in ann.keys(), please check your training annotation.")
             edges.append(ann.get('edge', 0))
         ann_infos = dict(
             image=data['image'],