fix ic15.yml and del img_words_en
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@ -36,12 +36,13 @@ Architecture:
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algorithm: CRNN
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Transform:
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Backbone:
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name: ResNet
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layers: 34
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name: MobileNetV3
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scale: 0.5
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model_name: large
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Neck:
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name: SequenceEncoder
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encoder_type: rnn
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hidden_size: 256
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hidden_size: 96
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Head:
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name: CTCHead
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fc_decay: 0
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@ -353,8 +353,7 @@ python3 tools/infer_rec.py -c configs/rec/rec_icdar15_train.yml -o Global.checkp
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```
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infer_img: doc/imgs_words/en/word_1.png
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index: [19 24 18 23 29]
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word : joint
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result: ('joint', 0.9998967)
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```
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预测使用的配置文件必须与训练一致,如您通过 `python3 tools/train.py -c configs/rec/ch_ppocr_v2.0/rec_chinese_lite_train_v2.0.yml` 完成了中文模型的训练,
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@ -373,6 +372,5 @@ python3 tools/infer_rec.py -c configs/rec/ch_ppocr_v2.0/rec_chinese_lite_train_v
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```
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infer_img: doc/imgs_words/ch/word_1.jpg
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index: [2092 177 312 2503]
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word : 韩国小馆
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result: ('韩国小馆', 0.997218)
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```
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@ -347,8 +347,7 @@ Get the prediction result of the input image:
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```
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infer_img: doc/imgs_words/en/word_1.png
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index: [19 24 18 23 29]
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word : joint
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result: ('joint', 0.9998967)
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```
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The configuration file used for prediction must be consistent with the training. For example, you completed the training of the Chinese model with `python3 tools/train.py -c configs/rec/ch_ppocr_v2.0/rec_chinese_lite_train_v2.0.yml`, you can use the following command to predict the Chinese model:
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@ -366,6 +365,5 @@ Get the prediction result of the input image:
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```
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infer_img: doc/imgs_words/ch/word_1.jpg
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index: [2092 177 312 2503]
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word : 韩国小馆
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result: ('韩国小馆', 0.997218)
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```
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