Merge pull request #1467 from LDOUBLEV/dyg_db

delete doc imgs and fix inference doc

doc/doc_ch/inference.md

@@ -131,12 +131,12 @@ python3 tools/export_model.py -c configs/cls/cls_mv3.yml -o Global.pretrained_mo
 # 下载超轻量中文检测模型：
 wget  https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_det_infer.tar
 tar xf ch_ppocr_mobile_v2.0_det_infer.tar
-python3 tools/infer/predict_det.py --image_dir="./doc/imgs/22.jpg" --det_model_dir="./ch_ppocr_mobile_v2.0_det_infer/"
+python3 tools/infer/predict_det.py --image_dir="./doc/imgs/00018069.jpg" --det_model_dir="./ch_ppocr_mobile_v2.0_det_infer/"
 ```
 
 可视化文本检测结果默认保存到`./inference_results`文件夹里面，结果文件的名称前缀为'det_res'。结果示例如下：
 
-![](../imgs_results/det_res_22.jpg)
+![](../imgs_results/det_res_00018069.jpg)
 
 通过参数`limit_type`和`det_limit_side_len`来对图片的尺寸进行限制，
 `litmit_type`可选参数为[`max`, `min`]，

doc/doc_en/inference_en.md

@@ -138,12 +138,12 @@ For lightweight Chinese detection model inference, you can execute the following
 wget  https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_det_infer.tar
 tar xf ch_ppocr_mobile_v2.0_det_infer.tar
 # predict
-python3 tools/infer/predict_det.py --image_dir="./doc/imgs/22.jpg" --det_model_dir="./inference/det_db/"
+python3 tools/infer/predict_det.py --image_dir="./doc/imgs/00018069.jpg" --det_model_dir="./inference/det_db/"
 ```
 
 The visual text detection results are saved to the ./inference_results folder by default, and the name of the result file is prefixed with'det_res'. Examples of results are as follows:
 
-![](../imgs_results/det_res_22.jpg)
+![](../imgs_results/det_res_00018069.jpg)
 
 You can use the parameters `limit_type` and `det_limit_side_len` to limit the size of the input image,
 The optional parameters of `litmit_type` are [`max`, `min`], and