diff --git a/doc/doc_ch/algorithm_overview.md b/doc/doc_ch/algorithm_overview.md
index ecb0e9dfefbfdef2f8cea273c4e3de468aa29415..dd21f4ed649193f8e5df27acaa2b9e25950983f4 100755
--- a/doc/doc_ch/algorithm_overview.md
+++ b/doc/doc_ch/algorithm_overview.md
@@ -99,9 +99,9 @@ PaddleOCR将**持续新增**支持OCR领域前沿算法与模型，**欢迎广
|SVTR|SVTR-Tiny| 89.25% | rec_svtr_tiny_none_ctc_en | [训练模型](https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/rec_svtr_tiny_none_ctc_en_train.tar) |
|ViTSTR|ViTSTR| 79.82% | rec_vitstr_none_ce | [训练模型](https://paddleocr.bj.bcebos.com/rec_vitstr_none_ce_train.tar) |
|ABINet|Resnet45| 90.75% | rec_r45_abinet | [训练模型](https://paddleocr.bj.bcebos.com/rec_r45_abinet_train.tar) |
-|VisionLAN|Resnet45| 90.30% | rec_r45_visionlan | [训练模型](https://paddleocr.bj.bcebos.com/rec_r45_visionlan_train.tar) |
-|SPIN|ResNet32| 90.00% | rec_r32_gaspin_bilstm_att | coming soon |
-|RobustScanner|ResNet31| 87.77% | rec_r31_robustscanner | coming soon |
+|VisionLAN|Resnet45| 90.30% | rec_r45_visionlan | [训练模型](https://paddleocr.bj.bcebos.com/VisionLAN/rec_r45_visionlan_train.tar) |
+|SPIN|ResNet32| 90.00% | rec_r32_gaspin_bilstm_att | [训练模型](https://paddleocr.bj.bcebos.com/contribution/rec_r32_gaspin_bilstm_att.tar) |
+|RobustScanner|ResNet31| 87.77% | rec_r31_robustscanner | [训练模型](https://paddleocr.bj.bcebos.com/contribution/rec_r31_robustscanner.tar)|
diff --git a/doc/doc_ch/algorithm_rec_visionlan.md b/doc/doc_ch/algorithm_rec_visionlan.md
index 84b5ef68216972da982f9f1d902fddea7e107be9..b4474c29f8596197fb536f07fa96b9926e5b20f4 100644
--- a/doc/doc_ch/algorithm_rec_visionlan.md
+++ b/doc/doc_ch/algorithm_rec_visionlan.md
@@ -27,7 +27,7 @@
|模型|骨干网络|配置文件|Acc|下载链接|
| --- | --- | --- | --- | --- |
-|VisionLAN|ResNet45|[rec_r45_visionlan.yml](../../configs/rec/rec_r45_visionlan.yml)|90.3%|[预训练、训练模型](https://paddleocr.bj.bcebos.com/rec_r45_visionlan_train.tar)|
+|VisionLAN|ResNet45|[rec_r45_visionlan.yml](../../configs/rec/rec_r45_visionlan.yml)|90.3%|[预训练、训练模型](https://paddleocr.bj.bcebos.com/VisionLAN/rec_r45_visionlan_train.tar)|
## 2. 环境配置
@@ -80,7 +80,7 @@ python3 tools/infer_rec.py -c configs/rec/rec_r45_visionlan.yml -o Global.infer_
### 4.1 Python推理
-首先将训练得到best模型，转换成inference model。这里以训练完成的模型为例（[模型下载地址](https://paddleocr.bj.bcebos.com/rec_r45_visionlan_train.tar))，可以使用如下命令进行转换：
+首先将训练得到best模型，转换成inference model。这里以训练完成的模型为例（[模型下载地址](https://paddleocr.bj.bcebos.com/VisionLAN/rec_r45_visionlan_train.tar))，可以使用如下命令进行转换：
```shell
# 注意将pretrained_model的路径设置为本地路径。
diff --git a/doc/doc_en/algorithm_overview_en.md b/doc/doc_en/algorithm_overview_en.md
index bca22f78482980bed18d6447d0cf07b27c26720d..42ccbe933d39a5c69d895aa9ef9c5c06c77d1cb8 100755
--- a/doc/doc_en/algorithm_overview_en.md
+++ b/doc/doc_en/algorithm_overview_en.md
@@ -96,9 +96,9 @@ Refer to [DTRB](https://arxiv.org/abs/1904.01906), the training and evaluation r
|SVTR|SVTR-Tiny| 89.25% | rec_svtr_tiny_none_ctc_en | [trained model](https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/rec_svtr_tiny_none_ctc_en_train.tar) |
|ViTSTR|ViTSTR| 79.82% | rec_vitstr_none_ce | [trained model](https://paddleocr.bj.bcebos.com/rec_vitstr_none_none_train.tar) |
|ABINet|Resnet45| 90.75% | rec_r45_abinet | [trained model](https://paddleocr.bj.bcebos.com/rec_r45_abinet_train.tar) |
-|VisionLAN|Resnet45| 90.30% | rec_r45_visionlan | [trained model](https://paddleocr.bj.bcebos.com/rec_r45_visionlan_train.tar) |
-|SPIN|ResNet32| 90.00% | rec_r32_gaspin_bilstm_att | coming soon |
-|RobustScanner|ResNet31| 87.77% | rec_r31_robustscanner | coming soon |
+|VisionLAN|Resnet45| 90.30% | rec_r45_visionlan | [trained model](https://paddleocr.bj.bcebos.com/VisionLAN/rec_r45_visionlan_train.tar) |
+|SPIN|ResNet32| 90.00% | rec_r32_gaspin_bilstm_att | [trained model](https://paddleocr.bj.bcebos.com/contribution/rec_r32_gaspin_bilstm_att.tar) |
+|RobustScanner|ResNet31| 87.77% | rec_r31_robustscanner | [trained model](https://paddleocr.bj.bcebos.com/contribution/rec_r31_robustscanner.tar)|
diff --git a/doc/doc_en/algorithm_rec_visionlan_en.md b/doc/doc_en/algorithm_rec_visionlan_en.md
index cf2293b3d091820d5a91a78834f501f1ac8da9dd..f67aa3c622d706a387075b37bd9e493740574cdd 100644
--- a/doc/doc_en/algorithm_rec_visionlan_en.md
+++ b/doc/doc_en/algorithm_rec_visionlan_en.md
@@ -25,7 +25,7 @@ Using MJSynth and SynthText two text recognition datasets for training, and eval
|Model|Backbone|config|Acc|Download link|
| --- | --- | --- | --- | --- |
-|VisionLAN|ResNet45|[rec_r45_visionlan.yml](../../configs/rec/rec_r45_visionlan.yml)|90.3%|[预训练、训练模型](https://paddleocr.bj.bcebos.com/rec_r45_visionlan_train.tar)|
+|VisionLAN|ResNet45|[rec_r45_visionlan.yml](../../configs/rec/rec_r45_visionlan.yml)|90.3%|[预训练、训练模型](https://paddleocr.bj.bcebos.com/VisionLAN/rec_r45_visionlan_train.tar)|
## 2. Environment
@@ -68,7 +68,7 @@ python3 tools/infer_rec.py -c configs/rec/rec_r45_visionlan.yml -o Global.infer_
### 4.1 Python Inference
-First, the model saved during the VisionLAN text recognition training process is converted into an inference model. ( [Model download link](https://paddleocr.bj.bcebos.com/rec_r45_visionlan_train.tar)) ), you can use the following command to convert:
+First, the model saved during the VisionLAN text recognition training process is converted into an inference model. ( [Model download link](https://paddleocr.bj.bcebos.com/VisionLAN/rec_r45_visionlan_train.tar)) ), you can use the following command to convert:
```
python3 tools/export_model.py -c configs/rec/rec_r45_visionlan.yml -o Global.pretrained_model=./rec_r45_visionlan_train/best_accuracy Global.save_inference_dir=./inference/rec_r45_visionlan/
diff --git a/ppocr/data/imaug/label_ops.py b/ppocr/data/imaug/label_ops.py
index 8191e4c3753a16c9bbff6b98f1f59a64f4b4e0f3..a4027d1a3c2ade5c7c7a6973131580f382aa1205 100644
--- a/ppocr/data/imaug/label_ops.py
+++ b/ppocr/data/imaug/label_ops.py
@@ -107,7 +107,6 @@ class BaseRecLabelEncode(object):
self.beg_str = "sos"
self.end_str = "eos"
self.lower = lower
- self.use_default_dict = False
if character_dict_path is None:
logger = get_logger()
@@ -117,11 +116,8 @@ class BaseRecLabelEncode(object):
self.character_str = "0123456789abcdefghijklmnopqrstuvwxyz"
dict_character = list(self.character_str)
self.lower = True
- self.use_default_dict = True
else:
self.character_str = []
- if 'ppocr/utils/ic15_dict.txt' in character_dict_path:
- self.use_default_dict = True
with open(character_dict_path, "rb") as fin:
lines = fin.readlines()
for line in lines:
@@ -1348,9 +1344,6 @@ class VLLabelEncode(BaseRecLabelEncode):
**kwargs):
super(VLLabelEncode, self).__init__(
max_text_length, character_dict_path, use_space_char, lower)
- if self.use_default_dict:
- self.character = self.character[10:] + self.character[
- 1:10] + [self.character[0]]
self.dict = {}
for i, char in enumerate(self.character):
self.dict[char] = i
diff --git a/ppocr/postprocess/rec_postprocess.py b/ppocr/postprocess/rec_postprocess.py
index db9e20cbc45774c019784d9f2f19f6c2bb484759..631f158fd1c15e224b1086b3db4df7a5ea5fe6f9 100644
--- a/ppocr/postprocess/rec_postprocess.py
+++ b/ppocr/postprocess/rec_postprocess.py
@@ -26,15 +26,11 @@ class BaseRecLabelDecode(object):
self.end_str = "eos"
self.reverse = False
self.character_str = []
- self.use_default_dict = False
if character_dict_path is None:
self.character_str = "0123456789abcdefghijklmnopqrstuvwxyz"
dict_character = list(self.character_str)
- self.use_default_dict = True
else:
- if 'ppocr/utils/ic15_dict.txt' in character_dict_path:
- self.use_default_dict = True
with open(character_dict_path, "rb") as fin:
lines = fin.readlines()
for line in lines:
@@ -725,9 +721,6 @@ class VLLabelDecode(BaseRecLabelDecode):
super(VLLabelDecode, self).__init__(character_dict_path, use_space_char)
self.max_text_length = kwargs.get('max_text_length', 25)
self.nclass = len(self.character) + 1
- if self.use_default_dict:
- self.character = self.character[10:] + self.character[
- 1:10] + [self.character[0]]
def decode(self, text_index, text_prob=None, is_remove_duplicate=False):
""" convert text-index into text-label. """