fix ref link

Topdu · Nov 23, 2024 · fa2b13e · fa2b13e
1 parent 256766c
commit fa2b13e
Show file tree

Hide file tree

Showing 3 changed files with 28 additions and 28 deletions.
diff --git a/README.md b/README.md
@@ -7,7 +7,7 @@ We sincerely welcome the researcher to recommend OCR or relevant algorithms and
 ## Features
 
 - 🔥**OpenOCR: A general OCR system for accuracy and efficiency**
-  - ⚡\[[Quick Start](<>)\] \[[Demo](<>)\]
+  - ⚡\[[Quick Start](./docs/openocr.md#quick-start)\] \[[Demo](<>)\]
   - [Introduction](./docs/openocr.md)
     - A practical version of the model builds on SVTRv2.
     - Outperforming [PP-OCRv4](<>) released by [PaddleOCR](<>) by 4.5% on the [OCR competition leaderboard](<>).
@@ -16,14 +16,14 @@ We sincerely welcome the researcher to recommend OCR or relevant algorithms and
     - [ ] Fine-tuning OpenOCR on a custom dataset
     - [ ] Export to ONNX engine
 - 🔥**SVTRv2: CTC Beats Encoder-Decoder Models in Scene Text Recognition**
-  - \[[Paper](./configs/rec/svtrv2/SVTRv2.pdf)\] \[[Model](../configs/rec/svtrv2/)\] \[[Config, Training and Inference](../configs/rec/svtrv2/)\]
+  - \[[Paper](../configs/rec/svtrv2/SVTRv2.pdf)\] \[[Model](./configs/rec/svtrv2/readme.md#11-models-and-results)\] \[[Config, Training and Inference](./configs/rec/svtrv2/readme.md#3-model-training--evaluation)\]
   - [Introduction](./docs/svtrv2.md)
     - Developing a unified training and evaluation benchmark for Scene Text Recognition
     - Supporting for 24 Scene Text Recognition methods trained from scratch on large-scale real datasets, and will continue to add the latest methods.
     - Improving results by 20-30% compared to training on synthetic datasets.
     - Towards Arbitrary-Shaped Text Recognition and Language modeling with a Single Visual Model.
     - Surpasses Attention-based Decoder Methods across challenging scenarios in terms of accuracy and speed
-  - [Get Started](./docs/svtrv2.md) with training a SoTA Scene Text Recognition model from scratch.
+  - [Get Started](./docs/svtrv2.md#get-started-with-training-a-sota-scene-text-recognition-model-from-scratch) with training a SoTA Scene Text Recognition model from scratch.
 
 ## Ours STR algorithms
 
@@ -41,15 +41,15 @@ We sincerely welcome the researcher to recommend OCR or relevant algorithms and
 ## Recent Updates
 
 - **🔥 2024.11.23 release notes**:
-  - 🔥**OpenOCR: A general OCR system for accuracy and efficiency**
-    - ⚡\[[Quick Start](./docs/openocr.md)\] \[[Demo](<>)\]
+  - **OpenOCR: A general OCR system for accuracy and efficiency**
+    - ⚡\[[Quick Start](./docs/openocr.md#quick-start)\] \[[Demo](<>)\]
     - [Introduction](./docs/openocr.md)
-  - 🔥**SVTRv2: CTC Beats Encoder-Decoder Models in Scene Text Recognition**
-    - \[[Paper](./configs/rec/svtrv2/SVTRv2.pdf)\] \[[Model](../configs/rec/svtrv2/)\] \[[Config, Training and Inference](../configs/rec/svtrv2/)\]
+  - **SVTRv2: CTC Beats Encoder-Decoder Models in Scene Text Recognition**
+    - \[[Paper](../configs/rec/svtrv2/SVTRv2.pdf)\] \[[Model](./configs/rec/svtrv2/readme.md#11-models-and-results)\] \[[Config, Training and Inference](./configs/rec/svtrv2/readme.md#3-model-training--evaluation)\]
     - [Introduction](./docs/svtrv2.md)
-    - [Get Started](./docs/svtrv2.md) with training a SoTA Scene Text Recognition model from scratch.
+    - [Get Started](./docs/svtrv2.md#get-started-with-training-a-sota-scene-text-recognition-model-from-scratch) with training a SoTA Scene Text Recognition model from scratch.
 
-## ⚡[Quick Start](./docs/openocr.md)
+## ⚡[Quick Start](./docs/openocr.md#quick-start)
 
 #### Dependencies:
 

diff --git a/configs/rec/svtrv2/readme.md b/configs/rec/svtrv2/readme.md
@@ -38,29 +38,29 @@ Download all Configs, Models, and Logs from [Google Drive](https://drive.google.
 
 - Test on Common Benchmarks from [PARSeq](https://github.com/baudm/parseq):
 
-|  Model   |                Training Data                 | IC13<br/>857 | SVT  | IIIT5k<br/>3000 | IC15<br/>1811 | SVTP | CUTE80 |  Avg  |                                     Config&Model&Log                                      |
-| :------: | :------------------------------------------: | :----------: | :--: | :-------------: | :-----------: | :--: | :----: | :---: | :---------------------------------------------------------------------------------------: |
-| SVTRv2-B |          Synthetic datasets (MJ+ST)          |     97.7     | 94.0 |      97.3       |     88.1      | 91.2 |  95.8  | 94.02 |                                           TODO                                            |
-| SVTRv2-T | [Union14M-L-Filter](../../../docs/svtrv2.md) |     98.6     | 96.6 |      98.0       |     88.4      | 90.5 |  96.5  | 94.78 | [Google drive](https://drive.google.com/drive/folders/12ZUGkCS7tEhFhWa2RKKtyB0tPjhH4d9s?usp=drive_link) |
-| SVTRv2-S | [Union14M-L-Filter](../../../docs/svtrv2.md) |     99.0     | 98.3 |      98.5       |     89.5      | 92.9 |  98.6  | 96.13 | [Google drive](https://drive.google.com/drive/folders/1mOG3EUAOsmD16B-VIelVDYf_O64q0G3M?usp=drive_link) |
-| SVTRv2-B | [Union14M-L-Filter](../../../docs/svtrv2.md) |     99.2     | 98.0 |      98.7       |     91.1      | 93.5 |  99.0  | 96.57 | [Google drive](https://drive.google.com/drive/folders/11u11ptDzQ4BF9RRsOYdZnXl6ell2h4jN?usp=drive_link) |
+|  Model   |                        Training Data                         | IC13<br/>857 | SVT  | IIIT5k<br/>3000 | IC15<br/>1811 | SVTP | CUTE80 |  Avg  |                             Config&Model&Log                              |
+| :------: | :----------------------------------------------------------: | :----------: | :--: | :-------------: | :-----------: | :--: | :----: | :---: | :-----------------------------------------------------------------------: |
+| SVTRv2-B |                  Synthetic datasets (MJ+ST)                  |     97.7     | 94.0 |      97.3       |     88.1      | 91.2 |  95.8  | 94.02 |                                   TODO                                    |
+| SVTRv2-T | [Union14M-L-Filter](../../../docs/svtrv2.md#dataset-details) |     98.6     | 96.6 |      98.0       |     88.4      | 90.5 |  96.5  | 94.78 | [Google drive](https://drive.google.com/drive/folders/12ZUGkCS7tEhFhWa2RKKtyB0tPjhH4d9s?usp=drive_link) |
+| SVTRv2-S | [Union14M-L-Filter](../../../docs/svtrv2.md#dataset-details) |     99.0     | 98.3 |      98.5       |     89.5      | 92.9 |  98.6  | 96.13 | [Google drive](https://drive.google.com/drive/folders/1mOG3EUAOsmD16B-VIelVDYf_O64q0G3M?usp=drive_link) |
+| SVTRv2-B | [Union14M-L-Filter](../../../docs/svtrv2.md#dataset-details) |     99.2     | 98.0 |      98.7       |     91.1      | 93.5 |  99.0  | 96.57 | [Google drive](https://drive.google.com/drive/folders/11u11ptDzQ4BF9RRsOYdZnXl6ell2h4jN?usp=drive_link) |
 
 - Test on Union14M-L benchmark from [Union14M](https://github.com/Mountchicken/Union14M/).
 
-|  Model   |                 Traing Data                  | Curve | Multi-<br/>Oriented | Artistic | Contextless | Salient | Multi-<br/>word | General |  Avg  |    Config&Model&Log     |
-| :------: | :------------------------------------------: | :---: | :-----------------: | :------: | :---------: | :-----: | :-------------: | :-----: | :---: | :---------------------: |
-| SVTRv2-B |          Synthetic datasets (MJ+ST)          | 74.6  |        25.2         |   57.6   |    69.7     |  77.9   |      68.0       |  66.9   | 62.83 | Same as the above table |
-| SVTRv2-T | [Union14M-L-Filter](../../../docs/svtrv2.md) | 83.6  |        76.0         |   71.2   |    82.4     |  77.2   |      82.3       |  80.7   | 79.05 | Same as the above table |
-| SVTRv2-S | [Union14M-L-Filter](../../../docs/svtrv2.md) | 88.3  |        84.6         |   76.5   |    84.3     |  83.3   |      85.4       |  83.5   | 83.70 | Same as the above table |
-| SVTRv2-B | [Union14M-L-Filter](../../../docs/svtrv2.md) | 90.6  |        89.0         |   79.3   |    86.1     |  86.2   |      86.7       |  85.1   | 86.14 | Same as the above table |
+|  Model   |                         Traing Data                          | Curve | Multi-<br/>Oriented | Artistic | Contextless | Salient | Multi-<br/>word | General |  Avg  |    Config&Model&Log     |
+| :------: | :----------------------------------------------------------: | :---: | :-----------------: | :------: | :---------: | :-----: | :-------------: | :-----: | :---: | :---------------------: |
+| SVTRv2-B |                  Synthetic datasets (MJ+ST)                  | 74.6  |        25.2         |   57.6   |    69.7     |  77.9   |      68.0       |  66.9   | 62.83 | Same as the above table |
+| SVTRv2-T | [Union14M-L-Filter](../../../docs/svtrv2.md#dataset-details) | 83.6  |        76.0         |   71.2   |    82.4     |  77.2   |      82.3       |  80.7   | 79.05 | Same as the above table |
+| SVTRv2-S | [Union14M-L-Filter](../../../docs/svtrv2.md#dataset-details) | 88.3  |        84.6         |   76.5   |    84.3     |  83.3   |      85.4       |  83.5   | 83.70 | Same as the above table |
+| SVTRv2-B | [Union14M-L-Filter](../../../docs/svtrv2.md#dataset-details) | 90.6  |        89.0         |   79.3   |    86.1     |  86.2   |      86.7       |  85.1   | 86.14 | Same as the above table |
 
 - Test on [LTB](../smtr/readme.md) and [OST](https://github.com/wangyuxin87/VisionLAN).
 
-|  Model   |                 Traing Data                  |  LTB  | OST  |    Config&Model&Log     |
-| :------: | :------------------------------------------: | :---: | :--: | :---------------------: |
-| SVTRv2-T | [Union14M-L-Filter](../../../docs/svtrv2.md) | 47.83 | 71.4 | Same as the above table |
-| SVTRv2-S | [Union14M-L-Filter](../../../docs/svtrv2.md) | 47.57 | 78.0 | Same as the above table |
-| SVTRv2-B | [Union14M-L-Filter](../../../docs/svtrv2.md) | 50.23 | 80.0 | Same as the above table |
+|  Model   |                         Traing Data                          |  LTB  | OST  |    Config&Model&Log     |
+| :------: | :----------------------------------------------------------: | :---: | :--: | :---------------------: |
+| SVTRv2-T | [Union14M-L-Filter](../../../docs/svtrv2.md#dataset-details) | 47.83 | 71.4 | Same as the above table |
+| SVTRv2-S | [Union14M-L-Filter](../../../docs/svtrv2.md#dataset-details) | 47.57 | 78.0 | Same as the above table |
+| SVTRv2-B | [Union14M-L-Filter](../../../docs/svtrv2.md#dataset-details) | 50.23 | 80.0 | Same as the above table |
 
 - Training and test on Chinese dataset, from [Chinese Benckmark](https://github.com/FudanVI/benchmarking-chinese-text-recognition).
 
@@ -93,7 +93,7 @@ pip install -r requirements.txt
 
 ### Dataset Preparation
 
-Referring to [Downloading Datasets](https://github.com/Topdu/OpenOCR/tree/main/docs/svtrv2.md#downloading-datasets)
+Referring to [Downloading Datasets](../../../docs/svtrv2.md#downloading-datasets)
 
 ### Training
 

diff --git a/docs/svtrv2.md b/docs/svtrv2.md
@@ -1,6 +1,6 @@
 # SVTRv2: CTC Beats Encoder-Decoder Models in Scene Text Recognition
 
-\[[Paper](../configs/rec/svtrv2/SVTRv2.pdf)\] \[[Model](../configs/rec/svtrv2/)\] \[[Config, Training and Inference](../configs/rec/svtrv2/)\]
+\[[Paper](../configs/rec/svtrv2/SVTRv2.pdf)\] \[[Model](../configs/rec/svtrv2/readme.md#11-models-and-results)\] \[[Config, Training and Inference](../configs/rec/svtrv2/readme.md#3-model-training--evaluation)\]
 
 ## Introduction