Merge branch 'develop' of https://github.com/PaddlePaddle/PaddleClas into fix_cpp_serving_bug

README_ch.md

@@ -37,7 +37,7 @@ Res2Net200_vd预训练模型Top-1精度高达85.1%。
 * 您可以扫描下面的微信群二维码， 加入PaddleClas 微信交流群。获得更高效的问题答疑，与各行各业开发者充分交流，期待您的加入。
 
 <div align="center">
-<img src="https://user-images.githubusercontent.com/12560511/150500411-fdb27d17-0c50-4ac1-a484-fb4a9c2454b3.jpg"  width = "200" />
+<img src="https://user-images.githubusercontent.com/12560511/151663044-165cf03e-5a9d-4d5d-bd5a-9dbac2ab5b30.jpeg"  width = "200" />
 </div>
 
 ## 快速体验

README_en.md

@@ -41,7 +41,7 @@ Four sample solutions are provided, including product recognition, vehicle recog
 * You can also scan the QR code below to join the PaddleClas WeChat group to get more efficient answers to your questions and to communicate with developers from all walks of life. We look forward to hearing from you.
 
 <div align="center">
-<img src="https://user-images.githubusercontent.com/12560511/150500411-fdb27d17-0c50-4ac1-a484-fb4a9c2454b3.jpg"  width = "200" />
+<img src="https://user-images.githubusercontent.com/12560511/151663044-165cf03e-5a9d-4d5d-bd5a-9dbac2ab5b30.jpeg"  width = "200" />
 </div>
 
 ## Quick Start

deploy/paddle2onnx/readme.md

@@ -52,7 +52,7 @@ python3.7 python/predict_cls.py \
 -c configs/inference_cls.yaml \
 -o Global.use_onnx=True \
 -o Global.use_gpu=False \
--o Global.inference_model_dir=./models/ResNet50_vd_infer \
+-o Global.inference_model_dir=./models/ResNet50_vd_infer
 ```
 
 结果如下：

docs/zh_CN/quick_start/quick_start_recognition.md

@@ -162,9 +162,8 @@ python3.7 python/predict_system.py -c configs/inference_general.yaml -o Global.u
 
 待检索图像如下所示。
 
-<div align="center">
-<img src="../../images/recognition/drink_data_demo/test_images/nongfu_spring.jpeg" width = "400" />
-</div>
+![](../../images/recognition/drink_data_demo/test_images/nongfu_spring.jpeg)
+
 
 最终输出结果如下。
 
@@ -176,9 +175,7 @@ python3.7 python/predict_system.py -c configs/inference_general.yaml -o Global.u
 
 检测的可视化结果也保存在 `output` 文件夹下，对于本张图像，识别结果可视化如下所示。
 
-<div align="center">
-<img src="../../images/recognition/drink_data_demo/output/nongfu_spring.jpeg" width = "400" />
-<div align="center">
+![](../../images/recognition/drink_data_demo/output/nongfu_spring.jpeg)
 
 
 <a name="基于文件夹的批量识别"></a>
@@ -227,9 +224,8 @@ python3.7 python/predict_system.py -c configs/inference_general.yaml -o Global.i
 
 待检索图像如下所示。
 
-<div align="center">
-<img src="../../images/recognition/drink_data_demo/test_images/mosilian.jpeg" width = "400" />
-</div>
+![](../../images/recognition/drink_data_demo/test_images/mosilian.jpeg)
+
 
 输出结果为空。
 
@@ -279,9 +275,8 @@ python3.7 python/predict_system.py -c configs/inference_general.yaml -o Global.i
 
 最终识别结果为`光明_莫斯利安`，识别正确，识别结果可视化如下所示。
 
-<div align="center">
-<img src="../../images/recognition/drink_data_demo/output/mosilian.jpeg" width = "400" />
-</div>
+![](../../images/recognition/drink_data_demo/output/mosilian.jpeg)
+
 
 <a name="4"></a>
 ## 4. 服务端识别模型列表