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rename text rec models
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configs/rec/SVTRv2/rec_repsvtr_ch.yml renamed to configs/rec/SVTRv2/ch_RepSVTR_rec.yml

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epoch_num: 200
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log_smooth_window: 20
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print_batch_step: 10
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save_model_dir: ./output/rec_repsvtr_ch
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save_model_dir: ./output/ch_RepSVTR_rec
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save_epoch_step: 10
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eval_batch_step: [0, 1000]
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cal_metric_during_train: False

configs/rec/SVTRv2/rec_repsvtr_gtc.yml renamed to configs/rec/SVTRv2/ch_RepSVTR_rec_gtc.yml

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epoch_num: 200
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log_smooth_window: 20
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print_batch_step: 10
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save_model_dir: ./output/rec_repsvtr_gtc
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save_model_dir: ./output/ch_RepSVTR_rec_gtc
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save_epoch_step: 10
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eval_batch_step: [0, 1000]
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cal_metric_during_train: False

configs/rec/SVTRv2/rec_svtrv2_ch.yml renamed to configs/rec/SVTRv2/ch_SVTRv2_rec.yml

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epoch_num: 200
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log_smooth_window: 20
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print_batch_step: 10
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save_model_dir: ./output/rec_svtrv2_ch
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save_model_dir: ./output/ch_SVTRv2_rec
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save_epoch_step: 10
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eval_batch_step: [0, 1000]
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cal_metric_during_train: False

configs/rec/SVTRv2/rec_svtrv2_ch_distillation.yml renamed to configs/rec/SVTRv2/ch_SVTRv2_rec_distillation.yml

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epoch_num: 100
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log_smooth_window: 20
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print_batch_step: 10
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save_model_dir: ./output/rec_svtrv2_ch_distill_lr00002/
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save_model_dir: ./output/ch_SVTRv2_rec_distill_lr00002/
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save_epoch_step: 5
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eval_batch_step:
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algorithm: Distillation
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Models:
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Teacher:
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pretrained: ./output/rec_svtrv2_ch/best_accuracy
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pretrained: ./output/ch_SVTRv2_rec/best_accuracy
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freeze_params: true
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return_all_feats: true
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model_type: rec
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num_decoder_layers: 2
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max_text_length: *max_text_length
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Student:
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pretrained: ./output/rec_repsvtr_ch/best_accuracy
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pretrained: ./output/ch_RepSVTR_rec/best_accuracy
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freeze_params: false
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return_all_feats: true
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model_type: rec

configs/rec/SVTRv2/rec_svtrv2_gtc.yml renamed to configs/rec/SVTRv2/ch_SVTRv2_rec_gtc.yml

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epoch_num: 200
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log_smooth_window: 20
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print_batch_step: 10
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save_model_dir: ./output/rec_svtrv2_gtc
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save_model_dir: ./output/ch_SVTRv2_rec_gtc
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save_epoch_step: 10
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eval_batch_step: [0, 1000]
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cal_metric_during_train: False

configs/rec/SVTRv2/rec_svtrv2_gtc_distill.yml renamed to configs/rec/SVTRv2/ch_SVTRv2_rec_gtc_distill.yml

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epoch_num: 100
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log_smooth_window: 20
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print_batch_step: 10
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save_model_dir: ./output/rec_svtrv2_gtc_distill_lr00002/
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save_model_dir: ./output/ch_SVTRv2_rec_gtc_distill_lr00002/
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save_epoch_step: 5
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eval_batch_step:
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algorithm: Distillation
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Models:
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Teacher:
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pretrained: ./output/rec_svtrv2_gtc/best_accuracy
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pretrained: ./output/ch_SVTRv2_rec_gtc/best_accuracy
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freeze_params: true
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return_all_feats: true
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model_type: rec
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num_decoder_layers: 2
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max_text_length: *max_text_length
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Student:
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pretrained: ./output/rec_repsvtr_gtc/best_accuracy
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pretrained: ./output/ch_RepSVTR_rec_gtc/best_accuracy
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freeze_params: false
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return_all_feats: true
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model_type: rec

docs/FAQ.md

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**A**: 推理时识别模型默认的batch_size=6, 如预测图片长度变化大,可能影响预测效果。如果出现上述问题可在推理的时候设置识别bs=1,命令如下:
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```bash linenums="1"
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python3 tools/infer/predict_rec.py --image_dir="./doc/imgs_words/ch/word_4.jpg" --rec_model_dir="./ch_PP-OCRv3_rec_infer/" --rec_batch_num=1
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python3 tools/infer/predict_rec.py --image_dir="./doc/imgs_words/ch/word_4.jpg" --rec_model_dir="./PP-OCRv3_mobile_rec_infer/" --rec_batch_num=1
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```
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### 2.13 推理部署

docs/algorithm/text_recognition/algorithm_rec_svtrv2.md

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|模型|配置文件|端到端|下载链接|
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| --- | --- | --- | --- |
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|PP-OCRv4| |A榜 62.77% <br> B榜 62.51%| [Model List](../../ppocr/model_list.md) |
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|SVTRv2(Rec Sever)|[configs/rec/SVTRv2/rec_svtrv2_ch.yml](https://github.com/PaddlePaddle/PaddleOCR/tree/main/configs/rec/SVTRv2/rec_svtrv2_ch.yml)|A榜 68.81% (使用PP-OCRv4检测模型)| [训练模型](https://paddleocr.bj.bcebos.com/openatom/openatom_rec_svtrv2_ch_train.tar) / [推理模型](https://paddleocr.bj.bcebos.com/openatom/openatom_rec_svtrv2_ch_infer.tar) |
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|RepSVTR(Mobile)|[识别](https://github.com/PaddlePaddle/PaddleOCR/tree/main/configs/rec/SVTRv2/rec_repsvtr_ch.yml) <br> [识别蒸馏](https://github.com/PaddlePaddle/PaddleOCR/tree/main/configs/rec/SVTRv2/rec_svtrv2_ch_distillation.yml) <br> [检测](https://github.com/PaddlePaddle/PaddleOCR/tree/main/configs/det/det_repsvtr_db.yml)|B榜 65.07%| 识别: [训练模型](https://paddleocr.bj.bcebos.com/openatom/openatom_rec_repsvtr_ch_train.tar) / [推理模型](https://paddleocr.bj.bcebos.com/openatom/openatom_rec_repsvtr_ch_infer.tar) <br> 识别蒸馏: [训练模型](https://paddleocr.bj.bcebos.com/openatom/openatom_rec_svtrv2_distill_ch_train.tar) / [推理模型](https://paddleocr.bj.bcebos.com/openatom/openatom_rec_svtrv2_distill_ch_infer.tar) <br> 检测: [训练模型](https://paddleocr.bj.bcebos.com/openatom/openatom_det_repsvtr_ch_train.tar) / [推理模型](https://paddleocr.bj.bcebos.com/openatom/openatom_det_repsvtr_ch_infer.tar) |
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|SVTRv2(Rec Sever)|[configs/rec/SVTRv2/ch_SVTRv2_rec.yml](https://github.com/PaddlePaddle/PaddleOCR/tree/main/configs/rec/SVTRv2/ch_SVTRv2_rec.yml)|A榜 68.81% (使用PP-OCRv4检测模型)| [训练模型](https://paddleocr.bj.bcebos.com/openatom/openatom_rec_svtrv2_ch_train.tar) / [推理模型](https://paddleocr.bj.bcebos.com/openatom/openatom_rec_svtrv2_ch_infer.tar) |
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|RepSVTR(Mobile)|[识别](https://github.com/PaddlePaddle/PaddleOCR/tree/main/configs/rec/SVTRv2/ch_RepSVTR_rec.yml) <br> [识别蒸馏](https://github.com/PaddlePaddle/PaddleOCR/tree/main/configs/rec/SVTRv2/ch_SVTRv2_rec_distillation.yml) <br> [检测](https://github.com/PaddlePaddle/PaddleOCR/tree/main/configs/det/det_repsvtr_db.yml)|B榜 65.07%| 识别: [训练模型](https://paddleocr.bj.bcebos.com/openatom/openatom_rec_repsvtr_ch_train.tar) / [推理模型](https://paddleocr.bj.bcebos.com/openatom/openatom_rec_repsvtr_ch_infer.tar) <br> 识别蒸馏: [训练模型](https://paddleocr.bj.bcebos.com/openatom/openatom_rec_svtrv2_distill_ch_train.tar) / [推理模型](https://paddleocr.bj.bcebos.com/openatom/openatom_rec_svtrv2_distill_ch_infer.tar) <br> 检测: [训练模型](https://paddleocr.bj.bcebos.com/openatom/openatom_det_repsvtr_ch_train.tar) / [推理模型](https://paddleocr.bj.bcebos.com/openatom/openatom_det_repsvtr_ch_infer.tar) |
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🚀 快速使用:参考PP-OCR推理[说明文档](https://github.com/PaddlePaddle/PaddleOCR/blob/main/doc/doc_ch/inference_ppocr.md),将检测和识别模型替换为上表中对应的RepSVTR或SVTRv2推理模型即可使用。
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```bash linenums="1"
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#单卡训练(训练周期长,不建议)
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python3 tools/train.py -c configs/rec/SVTRv2/rec_repsvtr_gtc.yml
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python3 tools/train.py -c configs/rec/SVTRv2/ch_RepSVTR_rec_gtc.yml
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# 多卡训练,通过--gpus参数指定卡号
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# Rec 学生模型
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python -m paddle.distributed.launch --gpus '0,1,2,3,4,5,6,7' tools/train.py -c configs/rec/SVTRv2/rec_repsvtr_gtc.yml
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python -m paddle.distributed.launch --gpus '0,1,2,3,4,5,6,7' tools/train.py -c configs/rec/SVTRv2/ch_RepSVTR_rec_gtc.yml
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# Rec 教师模型
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python -m paddle.distributed.launch --gpus '0,1,2,3,4,5,6,7' tools/train.py -c configs/rec/SVTRv2/rec_svtrv2_gtc.yml
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python -m paddle.distributed.launch --gpus '0,1,2,3,4,5,6,7' tools/train.py -c configs/rec/SVTRv2/ch_SVTRv2_rec_gtc.yml
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# Rec 蒸馏训练
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python -m paddle.distributed.launch --gpus '0,1,2,3,4,5,6,7' tools/train.py -c configs/rec/SVTRv2/rec_svtrv2_gtc_distill.yml
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python -m paddle.distributed.launch --gpus '0,1,2,3,4,5,6,7' tools/train.py -c configs/rec/SVTRv2/ch_SVTRv2_rec_gtc_distill.yml
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```
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### 3.2 评估
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```bash linenums="1"
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# 注意将pretrained_model的路径设置为本地路径。
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python3 -m paddle.distributed.launch --gpus '0' tools/eval.py -c configs/rec/SVTRv2/rec_repsvtr_gtc.yml -o Global.pretrained_model=output/rec_repsvtr_gtc/best_accuracy
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python3 -m paddle.distributed.launch --gpus '0' tools/eval.py -c configs/rec/SVTRv2/ch_RepSVTR_rec_gtc.yml -o Global.pretrained_model=output/ch_RepSVTR_rec_gtc/best_accuracy
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```
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### 3.3 预测
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# 注意将pretrained_model的路径设置为本地路径。
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python3 tools/infer_rec.py -c tools/eval.py -c configs/rec/SVTRv2/rec_repsvtr_gtc.yml -o Global.pretrained_model=output/rec_repsvtr_gtc/best_accuracy Global.infer_img='./doc/imgs_words_en/word_10.png'
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python3 tools/infer_rec.py -c tools/eval.py -c configs/rec/SVTRv2/ch_RepSVTR_rec_gtc.yml -o Global.pretrained_model=output/ch_RepSVTR_rec_gtc/best_accuracy Global.infer_img='./doc/imgs_words_en/word_10.png'
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# 预测文件夹下所有图像时,可修改infer_img为文件夹,如 Global.infer_img='./doc/imgs_words_en/'。
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python3 tools/export_model.py -c configs/rec/SVTRv2/ch_RepSVTR_rec_gtc.yml -o Global.pretrained_model=output/ch_RepSVTR_rec_gtc/best_accuracy Global.save_inference_dir=./inference/rec_repsvtr_infer
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**注意:** 如果您是在自己的数据集上训练的模型,并且调整了字典文件,请注意修改配置文件中的`character_dict_path`是否为所正确的字典文件。

docs/index.hi.md

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| मॉडल प्रस्तावना | मॉडल नाम | रिकमेंडिड सीन | डिटेक्शन मॉडल | रिकोगनाइजेशन मॉडल |
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| ------------------------------------------------------------ | ---------------------------- | ----------------- | ------------------------------------------------------------ | ------------------------------------------------------------ |
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| हिन्दी:हिन्दी अल्ट्रा-लाइटवेट PP-ओसीआरv3 सिस्टम (9.9M) | devanagari_PP-ओसीआरv3_xx | मोबाइल और सर्वर |[इन्फरन्स मॉडल](https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/Multilingual_PP-OCRv3_det_infer.tar) / [प्रशिक्षितमॉडल](https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/Multilingual_PP-OCRv3_det_distill_train.tar) | [इन्फरन्समॉडल](https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/devanagari_PP-OCRv3_rec_infer.tar) / [प्रशिक्षित मॉडल](https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/devanagari_PP-OCRv3_rec_train.tar) |
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| इंग्लिश अल्ट्रा- लाइट वेट PP-ओसीआरv3 मॉडल (13.4M) | en_PP-ओसीआरv3_xx | मोबाइल और सर्वर | [इन्फरन्स मॉडल](https://paddleocr.bj.bcebos.com/PP-OCRv3/english/en_PP-OCRv3_det_infer.tar) / [प्रशिक्षितमॉडल](https://paddleocr.bj.bcebos.com/PP-OCRv3/english/en_PP-OCRv3_det_distill_train.tar)| [इन्फरन्समॉडल](https://paddleocr.bj.bcebos.com/PP-OCRv3/english/en_PP-OCRv3_rec_infer.tar) / [प्रशिक्षित मॉडल](https://paddleocr.bj.bcebos.com/PP-OCRv3/english/en_PP-OCRv3_rec_train.tar) |
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| चाइनीस और इंग्लिश अल्ट्रा- लाइट वेट PP-ओसीआरv3 मॉडल(16.2M) | ch_PP-ओसीआरv3_xx | मोबाइल और सर्वर | [इन्फरन्स मॉडल](https://paddle-model-ecology.bj.bcebos.com/paddlex/official_inference_model/paddle3.0.0/PP-OCRv3_mobile_det_infer.tar) / [प्रशिक्षित मॉडल](https://paddle-model-ecology.bj.bcebos.com/paddlex/official_pretrained_model/PP-OCRv3_mobile_det_pretrained.pdparams) | [प्रशिक्षित मॉडल](https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_rec_infer.tar) / [प्रशिक्षित मॉडल](https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_rec_train.tar) |
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| इंग्लिश अल्ट्रा- लाइट वेट PP-ओसीआरv3 मॉडल (13.4M) | en_PP-ओसीआरv3_xx | मोबाइल और सर्वर | [इन्फरन्स मॉडल](https://paddleocr.bj.bcebos.com/PP-OCRv3/english/en_PP-OCRv3_det_infer.tar) / [प्रशिक्षितमॉडल](https://paddleocr.bj.bcebos.com/PP-OCRv3/english/en_PP-OCRv3_det_distill_train.tar)| [इन्फरन्समॉडल](https://paddle-model-ecology.bj.bcebos.com/paddlex/official_inference_model/paddle3.0.0/en_PP-OCRv3_mobile_rec_infer.tar) / [प्रशिक्षित मॉडल](https://paddleocr.bj.bcebos.com/PP-OCRv3/english/en_PP-OCRv3_rec_train.tar) |
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| चाइनीस और इंग्लिश अल्ट्रा- लाइट वेट PP-ओसीआरv3 मॉडल(16.2M) | ch_PP-ओसीआरv3_xx | मोबाइल और सर्वर | [इन्फरन्स मॉडल](https://paddle-model-ecology.bj.bcebos.com/paddlex/official_inference_model/paddle3.0.0/PP-OCRv3_mobile_det_infer.tar) / [प्रशिक्षित मॉडल](https://paddle-model-ecology.bj.bcebos.com/paddlex/official_pretrained_model/PP-OCRv3_mobile_det_pretrained.pdparams) | [प्रशिक्षित मॉडल](https://paddle-model-ecology.bj.bcebos.com/paddlex/official_inference_model/paddle3.0.0/PP-OCRv3_mobile_rec_infer.tar) / [प्रशिक्षित मॉडल](https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_rec_train.tar) |
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- अधिक मॉडल डाउनलोड (एकाधिक भाषाओं सहित) के लिए, कृपया [PP-ओसीआर सीरीज मॉडल डाउनलोड](../doc_en/models_list_en.md) देखें।
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- एक नए भाषा अनुरोध के लिए, कृपया [नई भाषा अनुरोधों के लिए दिशानिर्देश](#language_requests).

docs/index.ja.md

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| モデル紹介 | モデル名 | 推奨のシーン | 検出モデル | 認識モデル |
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| ------------------------------------------------------------ | ---------------------------- | ----------------- | ------------------------------------------------------------ | ------------------------------------------------------------ |
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| 日本語超軽量 PP-OCRv3 モデル(14.8M) | japan_PP-OCRv3_xx | モバイル & サーバー |[推論モデル](https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/Multilingual_PP-OCRv3_det_infer.tar)/[トレーニングモデル](https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/Multilingual_PP-OCRv3_det_distill_train.tar) |[推論モデル](https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/japan_PP-OCRv3_rec_infer.tar)/[トレーニングモデル](https://paddleocr.bj.bcebos.com/PP-OCRv3/multilingual/japan_PP-OCRv3_rec_train.tar) |
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| 英語超軽量PP-OCRv3モデル(13.4M) | en_PP-OCRv3_xx | モバイル & サーバー | [推論モデル](https://paddleocr.bj.bcebos.com/PP-OCRv3/english/en_PP-OCRv3_det_infer.tar) / [トレーニングモデル](https://paddleocr.bj.bcebos.com/PP-OCRv3/english/en_PP-OCRv3_det_distill_train.tar) | [推論モデル](https://paddleocr.bj.bcebos.com/PP-OCRv3/english/en_PP-OCRv3_rec_infer.tar) / [トレーニングモデル](https://paddleocr.bj.bcebos.com/PP-OCRv3/english/en_PP-OCRv3_rec_train.tar) |
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| 中国語と英語の超軽量 PP-OCRv3 モデル(16.2M) | ch_PP-OCRv3_xx | モバイル & サーバー | [推論モデル](https://paddle-model-ecology.bj.bcebos.com/paddlex/official_inference_model/paddle3.0.0/PP-OCRv3_mobile_det_infer.tar) / [トレーニングモデル](https://paddle-model-ecology.bj.bcebos.com/paddlex/official_pretrained_model/PP-OCRv3_mobile_det_pretrained.pdparams) | [推論モデル](https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_rec_infer.tar) / [トレーニングモデル](https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_rec_train.tar) |
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| 英語超軽量PP-OCRv3モデル(13.4M) | en_PP-OCRv3_xx | モバイル & サーバー | [推論モデル](https://paddleocr.bj.bcebos.com/PP-OCRv3/english/en_PP-OCRv3_det_infer.tar) / [トレーニングモデル](https://paddleocr.bj.bcebos.com/PP-OCRv3/english/en_PP-OCRv3_det_distill_train.tar) | [推論モデル](https://paddle-model-ecology.bj.bcebos.com/paddlex/official_inference_model/paddle3.0.0/en_PP-OCRv3_mobile_rec_infer.tar) / [トレーニングモデル](https://paddleocr.bj.bcebos.com/PP-OCRv3/english/en_PP-OCRv3_rec_train.tar) |
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| 中国語と英語の超軽量 PP-OCRv3 モデル(16.2M) | ch_PP-OCRv3_xx | モバイル & サーバー | [推論モデル](https://paddle-model-ecology.bj.bcebos.com/paddlex/official_inference_model/paddle3.0.0/PP-OCRv3_mobile_det_infer.tar) / [トレーニングモデル](https://paddle-model-ecology.bj.bcebos.com/paddlex/official_pretrained_model/PP-OCRv3_mobile_det_pretrained.pdparams) | [推論モデル](https://paddle-model-ecology.bj.bcebos.com/paddlex/official_inference_model/paddle3.0.0/PP-OCRv3_mobile_rec_infer.tar) / [トレーニングモデル](https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_rec_train.tar) |
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- その他のモデルのダウンロード (多言語を含む) については、[PP-OCR シリーズ モデルのダウンロード] (../doc_en/models_list_en.md)をご参照ください。
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- 新しい言語のリクエストについては、 [新しい言語_リクエストのガイドライン](#language_requests)を参照してください。

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