@@ -68,6 +68,7 @@ Supported text recognition algorithms (Click the link to get the tutorial):
...
@@ -68,6 +68,7 @@ Supported text recognition algorithms (Click the link to get the tutorial):
-[x] [SVTR](./algorithm_rec_svtr_en.md)
-[x] [SVTR](./algorithm_rec_svtr_en.md)
-[x] [ViTSTR](./algorithm_rec_vitstr_en.md)
-[x] [ViTSTR](./algorithm_rec_vitstr_en.md)
-[x] [ABINet](./algorithm_rec_abinet_en.md)
-[x] [ABINet](./algorithm_rec_abinet_en.md)
-[x] [VisionLAN](./algorithm_rec_visionlan_en.md)
-[x] [SPIN](./algorithm_rec_spin_en.md)
-[x] [SPIN](./algorithm_rec_spin_en.md)
Refer to [DTRB](https://arxiv.org/abs/1904.01906), the training and evaluation result of these above text recognition (using MJSynth and SynthText for training, evaluate on IIIT, SVT, IC03, IC13, IC15, SVTP, CUTE) is as follow:
Refer to [DTRB](https://arxiv.org/abs/1904.01906), the training and evaluation result of these above text recognition (using MJSynth and SynthText for training, evaluate on IIIT, SVT, IC03, IC13, IC15, SVTP, CUTE) is as follow:
...
@@ -89,6 +90,7 @@ Refer to [DTRB](https://arxiv.org/abs/1904.01906), the training and evaluation r
...
@@ -89,6 +90,7 @@ Refer to [DTRB](https://arxiv.org/abs/1904.01906), the training and evaluation r
Using MJSynth and SynthText two text recognition datasets for training, and evaluating on IIIT, SVT, IC13, IC15, SVTP, CUTE datasets, the algorithm reproduction effect is as follows:
Please refer to ["Environment Preparation"](./environment_en.md) to configure the PaddleOCR environment, and refer to ["Project Clone"](./clone_en.md) to clone the project code.
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## 3. Model Training / Evaluation / Prediction
Please refer to [Text Recognition Tutorial](./recognition_en.md). PaddleOCR modularizes the code, and training different recognition models only requires **changing the configuration file**.
Training:
Specifically, after the data preparation is completed, the training can be started. The training command is as follows:
```
#Single GPU training (long training period, not recommended)
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:
- If you are training the model on your own dataset and have modified the dictionary file, please pay attention to modify the `character_dict_path` in the configuration file to the modified dictionary file.
- If you modified the input size during training, please modify the `infer_shape` corresponding to VisionLAN in the `tools/export_model.py` file.
After the conversion is successful, there are three files in the directory:
```
./inference/rec_r45_visionlan/
├── inference.pdiparams
├── inference.pdiparams.info
└── inference.pdmodel
```
For VisionLAN text recognition model inference, the following commands can be executed:
