Skip to content

GitLab

Commit 80aced81 authored by Leif's avatar Leif
Browse files

Merge remote-tracking branch 'origin/dygraph' into dygraph

parents fce82425 896d149e
Hide whitespace changes
Inline Side-by-side
Showing with 90 additions and 79 deletions
doc/doc_en/quickstart_en.md
View file @ 80aced81
...@@ -73,6 +73,8 @@ cd /path/to/ppocr_img ...@@ -73,6 +73,8 @@ cd /path/to/ppocr_img
If you do not use the provided test image, you can replace the following `--image_dir` parameter with the corresponding test image path If you do not use the provided test image, you can replace the following `--image_dir` parameter with the corresponding test image path
**Note**: The whl package uses the `PP-OCRv3` model by default, and the input shape used by the recognition model is `3,48,320`, so if you use the recognition function, you need to add the parameter `--rec_image_shape 3,48,320`, if you do not use the default `PP- OCRv3` model, you do not need to set this parameter.
<a name="211-english-and-chinese-model"></a> <a name="211-english-and-chinese-model"></a>
#### 2.1.1 Chinese and English Model #### 2.1.1 Chinese and English Model
...@@ -80,15 +82,15 @@ If you do not use the provided test image, you can replace the following `--imag ...@@ -80,15 +82,15 @@ If you do not use the provided test image, you can replace the following `--imag
* Detection, direction classification and recognition: set the parameter`--use_gpu false` to disable the gpu device * Detection, direction classification and recognition: set the parameter`--use_gpu false` to disable the gpu device
```bash ```bash
paddleocr --image_dir ./imgs_en/img_12.jpg --use_angle_cls true --lang en --use_gpu false paddleocr --image_dir ./imgs_en/img_12.jpg --use_angle_cls true --lang en --use_gpu false --rec_image_shape 3,48,320
``` ```
Output will be a list, each item contains bounding box, text and recognition confidence Output will be a list, each item contains bounding box, text and recognition confidence
```bash ```bash
[[[442.0, 173.0], [1169.0, 173.0], [1169.0, 225.0], [442.0, 225.0]], ['ACKNOWLEDGEMENTS', 0.99283075]] [[[441.0, 174.0], [1166.0, 176.0], [1165.0, 222.0], [441.0, 221.0]], ('ACKNOWLEDGEMENTS', 0.9971134662628174)]
[[[393.0, 340.0], [1207.0, 342.0], [1207.0, 389.0], [393.0, 387.0]], ['We would like to thank all the designers and', 0.9357758]] [[[403.0, 346.0], [1204.0, 348.0], [1204.0, 384.0], [402.0, 383.0]], ('We would like to thank all the designers and', 0.9761400818824768)]
[[[399.0, 398.0], [1204.0, 398.0], [1204.0, 433.0], [399.0, 433.0]], ['contributors whohave been involved in the', 0.9592447]] [[[403.0, 396.0], [1204.0, 398.0], [1204.0, 434.0], [402.0, 433.0]], ('contributors who have been involved in the', 0.9791957139968872)]
...... ......
``` ```
...@@ -101,33 +103,33 @@ If you do not use the provided test image, you can replace the following `--imag ...@@ -101,33 +103,33 @@ If you do not use the provided test image, you can replace the following `--imag
Output will be a list, each item only contains bounding box Output will be a list, each item only contains bounding box
```bash ```bash
[[756.0, 812.0], [805.0, 812.0], [805.0, 830.0], [756.0, 830.0]] [[397.0, 802.0], [1092.0, 802.0], [1092.0, 841.0], [397.0, 841.0]]
[[820.0, 803.0], [1085.0, 801.0], [1085.0, 836.0], [820.0, 838.0]] [[397.0, 750.0], [1211.0, 750.0], [1211.0, 789.0], [397.0, 789.0]]
[[393.0, 801.0], [715.0, 805.0], [715.0, 839.0], [393.0, 836.0]] [[397.0, 702.0], [1209.0, 698.0], [1209.0, 734.0], [397.0, 738.0]]
...... ......
``` ```
* Only recognition: set `--det` to `false` * Only recognition: set `--det` to `false`
```bash ```bash
paddleocr --image_dir ./imgs_words_en/word_10.png --det false --lang en paddleocr --image_dir ./imgs_words_en/word_10.png --det false --lang en --rec_image_shape 3,48,320
``` ```
Output will be a list, each item contains text and recognition confidence Output will be a list, each item contains text and recognition confidence
```bash ```bash
['PAIN', 0.990372] ['PAIN', 0.9934559464454651]
``` ```
If you need to use the 2.0 model, please specify the parameter `--version PP-OCR`, paddleocr uses the 2.1 model by default(`--versioin PP-OCRv2`). More whl package usage can be found in [whl package](./whl_en.md) If you need to use the 2.0 model, please specify the parameter `--version PP-OCR`, paddleocr uses the PP-OCRv3 model by default(`--versioin PP-OCRv3`). More whl package usage can be found in [whl package](./whl_en.md)
<a name="212-multi-language-model"></a> <a name="212-multi-language-model"></a>
#### 2.1.2 Multi-language Model #### 2.1.2 Multi-language Model
Paddleocr currently supports 80 languages, which can be switched by modifying the `--lang` parameter. Paddleocr currently supports 80 languages, which can be switched by modifying the `--lang` parameter. PP-OCRv3 currently only supports Chinese and English models, and other multilingual models will be updated one after another.
``` bash ``` bash
paddleocr --image_dir ./doc/imgs_en/254.jpg --lang=en paddleocr --image_dir ./doc/imgs_en/254.jpg --lang=en --rec_image_shape 3,48,320
``` ```
<div align="center"> <div align="center">
...@@ -137,13 +139,9 @@ paddleocr --image_dir ./doc/imgs_en/254.jpg --lang=en ...@@ -137,13 +139,9 @@ paddleocr --image_dir ./doc/imgs_en/254.jpg --lang=en
The result is a list, each item contains a text box, text and recognition confidence The result is a list, each item contains a text box, text and recognition confidence
```text ```text
[('PHO CAPITAL', 0.95723116), [[66.0, 50.0], [327.0, 44.0], [327.0, 76.0], [67.0, 82.0]]] [[[67.0, 51.0], [327.0, 46.0], [327.0, 74.0], [68.0, 80.0]], ('PHOCAPITAL', 0.9944712519645691)]
[('107 State Street', 0.96311164), [[72.0, 90.0], [451.0, 84.0], [452.0, 116.0], [73.0, 121.0]]] [[[72.0, 92.0], [453.0, 84.0], [454.0, 114.0], [73.0, 122.0]], ('107 State Street', 0.9744491577148438)]
[('Montpelier Vermont', 0.97389287), [[69.0, 132.0], [501.0, 126.0], [501.0, 158.0], [70.0, 164.0]]] [[[69.0, 135.0], [501.0, 125.0], [501.0, 156.0], [70.0, 165.0]], ('Montpelier Vermont', 0.9357033967971802)]
[('8022256183', 0.99810505), [[71.0, 175.0], [363.0, 170.0], [364.0, 202.0], [72.0, 207.0]]]
[('REG 07-24-201706:59 PM', 0.93537045), [[73.0, 299.0], [653.0, 281.0], [654.0, 318.0], [74.0, 336.0]]]
[('045555', 0.99346405), [[509.0, 331.0], [651.0, 325.0], [652.0, 356.0], [511.0, 362.0]]]
[('CT1', 0.9988654), [[535.0, 367.0], [654.0, 367.0], [654.0, 406.0], [535.0, 406.0]]]
...... ......
``` ```
...@@ -234,10 +232,10 @@ im_show.save('result.jpg') ...@@ -234,10 +232,10 @@ im_show.save('result.jpg')
Output will be a list, each item contains bounding box, text and recognition confidence Output will be a list, each item contains bounding box, text and recognition confidence
```bash ```bash
[[[442.0, 173.0], [1169.0, 173.0], [1169.0, 225.0], [442.0, 225.0]], ['ACKNOWLEDGEMENTS', 0.99283075]] [[[441.0, 174.0], [1166.0, 176.0], [1165.0, 222.0], [441.0, 221.0]], ('ACKNOWLEDGEMENTS', 0.9971134662628174)]
[[[393.0, 340.0], [1207.0, 342.0], [1207.0, 389.0], [393.0, 387.0]], ['We would like to thank all the designers and', 0.9357758]] [[[403.0, 346.0], [1204.0, 348.0], [1204.0, 384.0], [402.0, 383.0]], ('We would like to thank all the designers and', 0.9761400818824768)]
[[[399.0, 398.0], [1204.0, 398.0], [1204.0, 433.0], [399.0, 433.0]], ['contributors whohave been involved in the', 0.9592447]] [[[403.0, 396.0], [1204.0, 398.0], [1204.0, 434.0], [402.0, 433.0]], ('contributors who have been involved in the', 0.9791957139968872)]
...... ......
``` ```
Visualization of results Visualization of results
......
doc/doc_en/recognition_en.md
View file @ 80aced81
# Text Recognition # Text Recognition
- [1. Data Preparation](#DATA_PREPARATION) - [1. Data Preparation](#DATA_PREPARATION)
* [1.1 Costom Dataset](#Costom_Dataset) * [1.1 Custom Dataset](#Custom_Dataset)
* [1.2 Dataset Download](#Dataset_download) * [1.2 Dataset Download](#Dataset_download)
* [1.3 Dictionary](#Dictionary) * [1.3 Dictionary](#Dictionary)
* [1.4 Add Space Category](#Add_space_category) * [1.4 Add Space Category](#Add_space_category)
...@@ -28,7 +28,34 @@ ...@@ -28,7 +28,34 @@
To prepare datasets, refer to [ocr_datasets](./dataset/ocr_datasets.md) . To prepare datasets, refer to [ocr_datasets](./dataset/ocr_datasets.md) .
If you want to reproduce the paper SAR, you need to download extra dataset [SynthAdd](https://pan.baidu.com/share/init?surl=uV0LtoNmcxbO-0YA7Ch4dg), extraction code: 627x. Besides, icdar2013, icdar2015, cocotext, IIIT5k datasets are also used to train. For specific details, please refer to the paper SAR. PaddleOCR provides label files for training the icdar2015 dataset, which can be downloaded in the following ways:
```
# Training set label
wget -P ./train_data/ic15_data https://paddleocr.bj.bcebos.com/dataset/rec_gt_train.txt
# Test Set Label
wget -P ./train_data/ic15_data https://paddleocr.bj.bcebos.com/dataset/rec_gt_test.txt
```
PaddleOCR also provides a data format conversion script, which can convert ICDAR official website label to a data format
supported by PaddleOCR. The data conversion tool is in `ppocr/utils/gen_label.py`, here is the training set as an example:
```
# convert the official gt to rec_gt_label.txt
python gen_label.py --mode="rec" --input_path="{path/of/origin/label}" --output_label="rec_gt_label.txt"
```
The data format is as follows, (a) is the original picture, (b) is the Ground Truth text file corresponding to each picture:
![](../datasets/icdar_rec.png)
- Multilingual dataset
The multi-language model training method is the same as the Chinese model. The training data set is 100w synthetic data. A small amount of fonts and test data can be downloaded using the following two methods.
* [Baidu Netdisk](https://pan.baidu.com/s/1bS_u207Rm7YbY33wOECKDA) ,Extraction code:frgi.
* [Google drive](https://drive.google.com/file/d/18cSWX7wXSy4G0tbKJ0d9PuIaiwRLHpjA/view)
<a name="Dictionary"></a> <a name="Dictionary"></a>
### 1.2 Dictionary ### 1.2 Dictionary
...@@ -101,11 +128,11 @@ First download the pretrain model, you can download the trained model to finetun ...@@ -101,11 +128,11 @@ First download the pretrain model, you can download the trained model to finetun
``` ```
cd PaddleOCR/ cd PaddleOCR/
# Download the pre-trained model of MobileNetV3 # Download the pre-trained model of en_PP-OCRv3
wget -P ./pretrain_models/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/rec_mv3_none_bilstm_ctc_v2.0_train.tar wget -P ./pretrain_models/ https://paddleocr.bj.bcebos.com/PP-OCRv3/english/en_PP-OCRv3_rec_train.tar
# Decompress model parameters # Decompress model parameters
cd pretrain_models cd pretrain_models
tar -xf rec_mv3_none_bilstm_ctc_v2.0_train.tar && rm -rf rec_mv3_none_bilstm_ctc_v2.0_train.tar tar -xf en_PP-OCRv3_rec_train.tar && rm -rf en_PP-OCRv3_rec_train.tar
``` ```
Start training: Start training:
...@@ -115,9 +142,10 @@ Start training: ...@@ -115,9 +142,10 @@ Start training:
# Training icdar15 English data and The training log will be automatically saved as train.log under "{save_model_dir}" # Training icdar15 English data and The training log will be automatically saved as train.log under "{save_model_dir}"
#specify the single card training(Long training time, not recommended) #specify the single card training(Long training time, not recommended)
python3 tools/train.py -c configs/rec/rec_icdar15_train.yml python3 tools/train.py -c configs/rec/PP-OCRv3/en_PP-OCRv3_rec.yml -o Global.pretrained_model=en_PP-OCRv3_rec_train/best_accuracy
#specify the card number through --gpus #specify the card number through --gpus
python3 -m paddle.distributed.launch --gpus '0,1,2,3' tools/train.py -c configs/rec/rec_icdar15_train.yml python3 -m paddle.distributed.launch --gpus '0,1,2,3' tools/train.py -c configs/rec/PP-OCRv3/en_PP-OCRv3_rec.yml -o Global.pretrained_model=en_PP-OCRv3_rec_train/best_accuracy
``` ```
...@@ -125,31 +153,13 @@ PaddleOCR supports alternating training and evaluation. You can modify `eval_bat ...@@ -125,31 +153,13 @@ PaddleOCR supports alternating training and evaluation. You can modify `eval_bat
If the evaluation set is large, the test will be time-consuming. It is recommended to reduce the number of evaluations, or evaluate after training. If the evaluation set is large, the test will be time-consuming. It is recommended to reduce the number of evaluations, or evaluate after training.
* Tip: You can use the `-c` parameter to select multiple model configurations under the `configs/rec/` path for training. The recognition algorithms supported by PaddleOCR are: * Tip: You can use the `-c` parameter to select multiple model configurations under the `configs/rec/` path for training. The recognition algorithms supported at [rec_algorithm](https://github.com/PaddlePaddle/PaddleOCR/blob/dygraph/doc/doc_en/algorithm_overview.md):
| Configuration file | Algorithm | backbone | trans | seq | pred |
| :--------: | :-------: | :-------: | :-------: | :-----: | :-----: |
| [rec_chinese_lite_train_v2.0.yml](../../configs/rec/ch_ppocr_v2.0/rec_chinese_lite_train_v2.0.yml) | CRNN | Mobilenet_v3 small 0.5 | None | BiLSTM | ctc |
| [rec_chinese_common_train_v2.0.yml](../../configs/rec/ch_ppocr_v2.0/rec_chinese_common_train_v2.0.yml) | CRNN | ResNet34_vd | None | BiLSTM | ctc |
| rec_chinese_lite_train.yml | CRNN | Mobilenet_v3 small 0.5 | None | BiLSTM | ctc |
| rec_chinese_common_train.yml | CRNN | ResNet34_vd | None | BiLSTM | ctc |
| rec_icdar15_train.yml | CRNN | Mobilenet_v3 large 0.5 | None | BiLSTM | ctc |
| rec_mv3_none_bilstm_ctc.yml | CRNN | Mobilenet_v3 large 0.5 | None | BiLSTM | ctc |
| rec_mv3_none_none_ctc.yml | Rosetta | Mobilenet_v3 large 0.5 | None | None | ctc |
| rec_r34_vd_none_bilstm_ctc.yml | CRNN | Resnet34_vd | None | BiLSTM | ctc |
| rec_r34_vd_none_none_ctc.yml | Rosetta | Resnet34_vd | None | None | ctc |
| rec_mv3_tps_bilstm_att.yml | CRNN | Mobilenet_v3 | TPS | BiLSTM | att |
| rec_r34_vd_tps_bilstm_att.yml | CRNN | Resnet34_vd | TPS | BiLSTM | att |
| rec_r50fpn_vd_none_srn.yml | SRN | Resnet50_fpn_vd | None | rnn | srn |
| rec_mtb_nrtr.yml | NRTR | nrtr_mtb | None | transformer encoder | transformer decoder |
| rec_r31_sar.yml | SAR | ResNet31 | None | LSTM encoder | LSTM decoder |
For training Chinese data, it is recommended to use For training Chinese data, it is recommended to use
[rec_chinese_lite_train_v2.0.yml](../../configs/rec/ch_ppocr_v2.0/rec_chinese_lite_train_v2.0.yml). If you want to try the result of other algorithms on the Chinese data set, please refer to the following instructions to modify the configuration file: [ch_PP-OCRv3_rec_distillation.yml](../../configs/rec/PP-OCRv3/ch_PP-OCRv3_rec_distillation.yml). If you want to try the result of other algorithms on the Chinese data set, please refer to the following instructions to modify the configuration file:
co
Take `rec_chinese_lite_train_v2.0.yml` as an example: Take `ch_PP-OCRv3_rec_distillation.yml` as an example:
``` ```
Global: Global:
... ...
...@@ -183,7 +193,7 @@ Train: ...@@ -183,7 +193,7 @@ Train:
... ...
- RecResizeImg: - RecResizeImg:
# Modify image_shape to fit long text # Modify image_shape to fit long text
image_shape: [3, 32, 320] image_shape: [3, 48, 320]
... ...
loader: loader:
... ...
...@@ -203,7 +213,7 @@ Eval: ...@@ -203,7 +213,7 @@ Eval:
... ...
- RecResizeImg: - RecResizeImg:
# Modify image_shape to fit long text # Modify image_shape to fit long text
image_shape: [3, 32, 320] image_shape: [3, 48, 320]
... ...
loader: loader:
# Eval batch_size for Single card # Eval batch_size for Single card
...@@ -380,11 +390,12 @@ Running on a DCU device requires setting the environment variable `export HIP_VI ...@@ -380,11 +390,12 @@ Running on a DCU device requires setting the environment variable `export HIP_VI
<a name="31-evaluation"></a> <a name="31-evaluation"></a>
### 3.1 Evaluation ### 3.1 Evaluation
The model parameters during training are saved in the `Global.save_model_dir` directory by default. When evaluating indicators, you need to set `Global.checkpoints` to point to the saved parameter file. The evaluation dataset can be set by modifying the `Eval.dataset.label_file_list` field in the `configs/rec/rec_icdar15_train.yml` file. The model parameters during training are saved in the `Global.save_model_dir` directory by default. When evaluating indicators, you need to set `Global.checkpoints` to point to the saved parameter file. The evaluation dataset can be set by modifying the `Eval.dataset.label_file_list` field in the `configs/rec/PP-OCRv3/en_PP-OCRv3_rec.yml` file.
``` ```
# GPU evaluation, Global.checkpoints is the weight to be tested # GPU evaluation, Global.checkpoints is the weight to be tested
python3 -m paddle.distributed.launch --gpus '0' tools/eval.py -c configs/rec/rec_icdar15_train.yml -o Global.checkpoints={path/to/weights}/best_accuracy python3 -m paddle.distributed.launch --gpus '0' tools/eval.py -c configs/rec/PP-OCRv3/en_PP-OCRv3_rec.yml -o Global.checkpoints={path/to/weights}/best_accuracy
``` ```
<a name="32-test"></a> <a name="32-test"></a>
...@@ -417,7 +428,7 @@ Among them, best_accuracy.* is the best model on the evaluation set; iter_epoch_ ...@@ -417,7 +428,7 @@ Among them, best_accuracy.* is the best model on the evaluation set; iter_epoch_
``` ```
# Predict English results # Predict English results
python3 tools/infer_rec.py -c configs/rec/ch_ppocr_v2.0/rec_chinese_lite_train_v2.0.yml -o Global.pretrained_model={path/to/weights}/best_accuracy Global.load_static_weights=false Global.infer_img=doc/imgs_words/en/word_1.jpg python3 tools/infer_rec.py -c configs/rec/PP-OCRv3/en_PP-OCRv3_rec.yml -o Global.pretrained_model={path/to/weights}/best_accuracy Global.infer_img=doc/imgs_words/en/word_1.png
``` ```
...@@ -436,7 +447,7 @@ The configuration file used for prediction must be consistent with the training. ...@@ -436,7 +447,7 @@ The configuration file used for prediction must be consistent with the training.
``` ```
# Predict Chinese results # Predict Chinese results
python3 tools/infer_rec.py -c configs/rec/ch_ppocr_v2.0/rec_chinese_lite_train_v2.0.yml -o Global.pretrained_model={path/to/weights}/best_accuracy Global.load_static_weights=false Global.infer_img=doc/imgs_words/ch/word_1.jpg python3 tools/infer_rec.py -c configs/rec/ch_ppocr_v2.0/rec_chinese_lite_train_v2.0.yml -o Global.pretrained_model={path/to/weights}/best_accuracy Global.infer_img=doc/imgs_words/ch/word_1.jpg
``` ```
Input image: Input image:
...@@ -467,7 +478,7 @@ The recognition model is converted to the inference model in the same way as the ...@@ -467,7 +478,7 @@ The recognition model is converted to the inference model in the same way as the
# Global.pretrained_model parameter Set the training model address to be converted without adding the file suffix .pdmodel, .pdopt or .pdparams. # Global.pretrained_model parameter Set the training model address to be converted without adding the file suffix .pdmodel, .pdopt or .pdparams.
# Global.save_inference_dir Set the address where the converted model will be saved. # Global.save_inference_dir Set the address where the converted model will be saved.
python3 tools/export_model.py -c configs/rec/ch_ppocr_v2.0/rec_chinese_lite_train_v2.0.yml -o Global.pretrained_model=./ch_lite/ch_ppocr_mobile_v2.0_rec_train/best_accuracy Global.save_inference_dir=./inference/rec_crnn/ python3 tools/export_model.py -c configs/rec/PP-OCRv3/en_PP-OCRv3_rec.yml -o Global.pretrained_model=en_PP-OCRv3_rec_train/best_accuracy Global.save_inference_dir=./inference/en_PP-OCRv3_rec/
``` ```
If you have a model trained on your own dataset with a different dictionary file, please make sure that you modify the `character_dict_path` in the configuration file to your dictionary file path. If you have a model trained on your own dataset with a different dictionary file, please make sure that you modify the `character_dict_path` in the configuration file to your dictionary file path.
...@@ -475,7 +486,8 @@ If you have a model trained on your own dataset with a different dictionary file ...@@ -475,7 +486,8 @@ If you have a model trained on your own dataset with a different dictionary file
After the conversion is successful, there are three files in the model save directory: After the conversion is successful, there are three files in the model save directory:
``` ```
inference/rec_crnn/
inference/en_PP-OCRv3_rec/
├── inference.pdiparams # The parameter file of recognition inference model ├── inference.pdiparams # The parameter file of recognition inference model
├── inference.pdiparams.info # The parameter information of recognition inference model, which can be ignored ├── inference.pdiparams.info # The parameter information of recognition inference model, which can be ignored
└── inference.pdmodel # The program file of recognition model └── inference.pdmodel # The program file of recognition model
......
doc/doc_en/whl_en.md
View file @ 80aced81
...@@ -172,40 +172,42 @@ show help information ...@@ -172,40 +172,42 @@ show help information
paddleocr -h paddleocr -h
``` ```
**Note**: The whl package uses the `PP-OCRv3` model by default, and the input shape used by the recognition model is `3,48,320`, so if you use the recognition function, you need to add the parameter `--rec_image_shape 3,48,320`, if you do not use the default `PP- OCRv3` model, you do not need to set this parameter.
* detection classification and recognition * detection classification and recognition
```bash ```bash
paddleocr --image_dir PaddleOCR/doc/imgs_en/img_12.jpg --use_angle_cls true --lang en paddleocr --image_dir PaddleOCR/doc/imgs_en/img_12.jpg --use_angle_cls true --lang en --rec_image_shape 3,48,320
``` ```
Output will be a list, each item contains bounding box, text and recognition confidence Output will be a list, each item contains bounding box, text and recognition confidence
```bash ```bash
[[[442.0, 173.0], [1169.0, 173.0], [1169.0, 225.0], [442.0, 225.0]], ['ACKNOWLEDGEMENTS', 0.99283075]] [[[441.0, 174.0], [1166.0, 176.0], [1165.0, 222.0], [441.0, 221.0]], ('ACKNOWLEDGEMENTS', 0.9971134662628174)]
[[[393.0, 340.0], [1207.0, 342.0], [1207.0, 389.0], [393.0, 387.0]], ['We would like to thank all the designers and', 0.9357758]] [[[403.0, 346.0], [1204.0, 348.0], [1204.0, 384.0], [402.0, 383.0]], ('We would like to thank all the designers and', 0.9761400818824768)]
[[[399.0, 398.0], [1204.0, 398.0], [1204.0, 433.0], [399.0, 433.0]], ['contributors whohave been involved in the', 0.9592447]] [[[403.0, 396.0], [1204.0, 398.0], [1204.0, 434.0], [402.0, 433.0]], ('contributors who have been involved in the', 0.9791957139968872)]
...... ......
``` ```
* detection and recognition * detection and recognition
```bash ```bash
paddleocr --image_dir PaddleOCR/doc/imgs_en/img_12.jpg --lang en paddleocr --image_dir PaddleOCR/doc/imgs_en/img_12.jpg --lang en --rec_image_shape 3,48,320
``` ```
Output will be a list, each item contains bounding box, text and recognition confidence Output will be a list, each item contains bounding box, text and recognition confidence
```bash ```bash
[[[442.0, 173.0], [1169.0, 173.0], [1169.0, 225.0], [442.0, 225.0]], ['ACKNOWLEDGEMENTS', 0.99283075]] [[[441.0, 174.0], [1166.0, 176.0], [1165.0, 222.0], [441.0, 221.0]], ('ACKNOWLEDGEMENTS', 0.9971134662628174)]
[[[393.0, 340.0], [1207.0, 342.0], [1207.0, 389.0], [393.0, 387.0]], ['We would like to thank all the designers and', 0.9357758]] [[[403.0, 346.0], [1204.0, 348.0], [1204.0, 384.0], [402.0, 383.0]], ('We would like to thank all the designers and', 0.9761400818824768)]
[[[399.0, 398.0], [1204.0, 398.0], [1204.0, 433.0], [399.0, 433.0]], ['contributors whohave been involved in the', 0.9592447]] [[[403.0, 396.0], [1204.0, 398.0], [1204.0, 434.0], [402.0, 433.0]], ('contributors who have been involved in the', 0.9791957139968872)]
...... ......
``` ```
* classification and recognition * classification and recognition
```bash ```bash
paddleocr --image_dir PaddleOCR/doc/imgs_words_en/word_10.png --use_angle_cls true --det false --lang en paddleocr --image_dir PaddleOCR/doc/imgs_words_en/word_10.png --use_angle_cls true --det false --lang en --rec_image_shape 3,48,320
``` ```
Output will be a list, each item contains text and recognition confidence Output will be a list, each item contains text and recognition confidence
```bash ```bash
['PAIN', 0.990372] ['PAIN', 0.9934559464454651]
``` ```
* only detection * only detection
...@@ -215,20 +217,20 @@ paddleocr --image_dir PaddleOCR/doc/imgs_en/img_12.jpg --rec false ...@@ -215,20 +217,20 @@ paddleocr --image_dir PaddleOCR/doc/imgs_en/img_12.jpg --rec false
Output will be a list, each item only contains bounding box Output will be a list, each item only contains bounding box
```bash ```bash
[[756.0, 812.0], [805.0, 812.0], [805.0, 830.0], [756.0, 830.0]] [[397.0, 802.0], [1092.0, 802.0], [1092.0, 841.0], [397.0, 841.0]]
[[820.0, 803.0], [1085.0, 801.0], [1085.0, 836.0], [820.0, 838.0]] [[397.0, 750.0], [1211.0, 750.0], [1211.0, 789.0], [397.0, 789.0]]
[[393.0, 801.0], [715.0, 805.0], [715.0, 839.0], [393.0, 836.0]] [[397.0, 702.0], [1209.0, 698.0], [1209.0, 734.0], [397.0, 738.0]]
...... ......
``` ```
* only recognition * only recognition
```bash ```bash
paddleocr --image_dir PaddleOCR/doc/imgs_words_en/word_10.png --det false --lang en paddleocr --image_dir PaddleOCR/doc/imgs_words_en/word_10.png --det false --lang en --rec_image_shape 3,48,320
``` ```
Output will be a list, each item contains text and recognition confidence Output will be a list, each item contains text and recognition confidence
```bash ```bash
['PAIN', 0.990372] ['PAIN', 0.9934559464454651]
``` ```
* only classification * only classification
...@@ -366,5 +368,4 @@ im_show.save('result.jpg') ...@@ -366,5 +368,4 @@ im_show.save('result.jpg')
| cls | Enable classification when `ppocr.ocr` func exec((Use use_angle_cls in command line mode to control whether to start classification in the forward direction) | FALSE | | cls | Enable classification when `ppocr.ocr` func exec((Use use_angle_cls in command line mode to control whether to start classification in the forward direction) | FALSE |
| show_log | Whether to print log| FALSE | | show_log | Whether to print log| FALSE |
| type | Perform ocr or table structuring, the value is selected in ['ocr','structure'] | ocr | | type | Perform ocr or table structuring, the value is selected in ['ocr','structure'] | ocr |
| ocr_version | OCR Model version number, the current model support list is as follows: PP-OCRv2 support Chinese detection and recognition model, PP-OCR support Chinese detection, recognition and direction classifier, multilingual recognition model | PP-OCRv2 | | ocr_version | OCR Model version number, the current model support list is as follows: PP-OCRv3 support Chinese and English detection and recognition model and direction classifier model, PP-OCRv2 support Chinese detection and recognition model, PP-OCR support Chinese detection, recognition and direction classifier, multilingual recognition model | PP-OCRv3 |
| structure_version | table structure Model version number, the current model support list is as follows: STRUCTURE support english table structure model | STRUCTURE |
doc/features.png
View replaced file @ fce82425 View file @ 80aced81
doc/features.png

1.15 MB | W: | H:

doc/features.png

1.36 MB | W: | H:

doc/features.png
doc/features.png
doc/features.png
doc/features.png
  • 2-up
  • Swipe
  • Onion skin
doc/features_en.png
View replaced file @ fce82425 View file @ 80aced81
doc/features_en.png

1.19 MB | W: | H:

doc/features_en.png

1.41 MB | W: | H:

doc/features_en.png
doc/features_en.png
doc/features_en.png
doc/features_en.png
  • 2-up
  • Swipe
  • Onion skin
notebook/notebook_ch/1.introduction/OCR技术导论.ipynb
View file @ 80aced81
...@@ -164,7 +164,7 @@ ...@@ -164,7 +164,7 @@
"\n", "\n",
"<br>\n", "<br>\n",
"\n", "\n",
"一般的KIE方法基于命名实体识别(Named Entity Recognition,NER)[4]来研究，但是这类方法只利用了图像中的文本信息，缺少对视觉和结构信息的使用，因此精度不高。在此基础上，近几年的方法都开始将视觉和结构信息与文本信息融合到一起，按照对多模态信息进行融合时所采用的的原理可以将这些方法分为下面四种：\n", "一般的KIE方法基于命名实体识别(Named Entity Recognition,NER)[4]来研究，但是这类方法只利用了图像中的文本信息，缺少对视觉和结构信息的使用，因此精度不高。在此基础上，近几年的方法都开始将视觉和结构信息与文本信息融合到一起，按照对多模态信息进行融合时所采用的原理可以将这些方法分为下面四种：\n",
"\n", "\n",
"- 基于Grid的方法\n", "- 基于Grid的方法\n",
"- 基于Token的方法\n", "- 基于Token的方法\n",
......
notebook/notebook_ch/3.text_recognition/文本识别实践部分.ipynb
View file @ 80aced81
...@@ -2133,7 +2133,7 @@ ...@@ -2133,7 +2133,7 @@
"collapsed": false "collapsed": false
}, },
"source": [ "source": [
"根据配置文件中设置的的 `save_model_dir` 字段，会有以下几种参数被保存下来：\n", "根据配置文件中设置的 `save_model_dir` 字段，会有以下几种参数被保存下来：\n",
"\n", "\n",
"```\n", "```\n",
"output/rec/ic15\n", "output/rec/ic15\n",
......
Markdown is supported
0% or .
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment