Merge pull request #1481 from felixhjh/dev_2

Dev 2

doc/DOCKER_IMAGES.md

@@ -37,7 +37,7 @@ If you want to customize your Serving based on source code, use the version with
 |              GPU (cuda10.1-cudnn7-tensorRT6-gcc54) development               | Ubuntu16 | latest-cuda10.1-cudnn7-gcc54-devel(not ready) | [Dockerfile.cuda10.1-cudnn7-gcc54.devel](../tools/Dockerfile.cuda10.1-cudnn7-gcc54.devel) |
 |              GPU (cuda10.1-cudnn7-tensorRT6) development               | Ubuntu16 | latest-cuda10.1-cudnn7-devel | [Dockerfile.cuda10.1-cudnn7.devel](../tools/Dockerfile.cuda10.1-cudnn7.devel) |
 |              GPU (cuda10.2-cudnn8-tensorRT7) development               | Ubuntu16 | latest-cuda10.2-cudnn8-devel | [Dockerfile.cuda10.2-cudnn8.devel](../tools/Dockerfile.cuda10.2-cudnn8.devel) |
-|              GPU (cuda11-cudnn8-tensorRT7) development               | Ubuntu18 | latest-cuda11-cudnn8-devel | [Dockerfile.cuda11-cudnn8.devel](../tools/Dockerfile.cuda11-cudnn8.devel) |
+|              GPU (cuda11.2-cudnn8-tensorRT7) development               | Ubuntu18 | latest-cuda11.2-cudnn8-devel | [Dockerfile.cuda11.2-cudnn8.devel](../tools/Dockerfile.cuda11.2-cudnn8.devel) |
 
 **Java Client:**
 ```

doc/HTTP_SERVICE_CN.md

@@ -48,7 +48,7 @@ python3.6 -m paddle_serving_server.serve --model uci_housing_model --thread 10 -
 
 Python的HttpClient使用示例见[`python/examples/fit_a_line/test_httpclient.py`](../python/examples/fit_a_line/test_httpclient.py)，接口详见[`python/paddle_serving_client/httpclient.py`](../python/paddle_serving_client/httpclient.py)。
 
-Java的HttpClient使用示例见[`java/examples/src/main/java/PaddleServingClientExample.java`](../java/examples/src/main/java/PaddleServingClientExample.java)接口详见[`java/src/main/java/io/paddle/serving/client/HttpClient.java`](../java/src/main/java/io/paddle/serving/client/HttpClient.java)。
+Java的HttpClient使用示例见[`java/examples/src/main/java/PaddleServingClientExample.java`](../java/examples/src/main/java/PaddleServingClientExample.java)接口详见[`java/src/main/java/io/paddle/serving/client/Client.java`](../java/src/main/java/io/paddle/serving/client/Client.java)。
 
 如果不能满足您的需求，您也可以在此基础上添加一些功能。
 

doc/model_zoo.md

+# Model Zoo
+
+本页面展示了Paddle Serving目前支持的预训练模型以及下载链接
+若您想为Paddle Serving提供新的模型，可通过[pull requese](https://github.com/PaddlePaddle/Serving/pulls)提交PR
+
+*特别感谢[PadddlePaddle 全链条](https://www.paddlepaddle.org.cn/wholechain)以及[PaddleHub](https://www.paddlepaddle.org.cn/hub)为Paddle Serving提供的部分预训练模型*
+
+
+| Model | Type | Dataset | Size | Download | Sample Input| Model mode |
+| --- | --- | --- | --- | --- | --- | --- |
+| ResNet_V2_50 | PaddleClas | ImageNet | 90.78 MB | [.tar.gz](https://paddle-serving.bj.bcebos.com/paddle_hub_models/image/ImageClassification/resnet_v2_50_imagenet.tar.gz) | [daisy.jpg](../examples/PaddleClas/resnet_v2_50/daisy.jpg) |Eager|
+| MobileNet_v2 | PaddleClas | ImageNet | 8.06 MB | [.tar.gz](https://paddle-serving.bj.bcebos.com/paddle_hub_models/image/ImageClassification/mobilenet_v2_imagenet.tar.gz) | [daisy.jpg](../examples/PaddleClas/mobilenet/daisy.jpg) |Eager|
+| Bert | PaddleNLP | zhwiki | 361.96 MB | [.tar.gz](https://paddle-serving.bj.bcebos.com/paddle_hub_models/text/SemanticModel/bert_chinese_L-12_H-768_A-12.tar.gz) | [data-c.txt](../examples/PaddleNLP/data-c.txt) |Eager|
+| Senta | PaddleNLP | Baidu | 578.37 MB | [.tar.gz](https://paddle-serving.bj.bcebos.com/paddle_hub_models/text/SentimentAnalysis/senta_bilstm.tar.gz) |  |Eager|
+| Squeezenet 1_1 | Image Classification | ImageNet | 4.4 MB | [.mar](https://torchserve.pytorch.org/mar_files/squeezenet1_1.mar) | [kitten.jpg](../examples/image_classifier/kitten.jpg) |Eager|
+| MNIST digit classifier | Image Classification | MNIST | 4.3 MB | [.mar](https://torchserve.pytorch.org/mar_files/mnist_v2.mar) | [0.png](../examples/image_classifier/mnist/test_data/0.png) |Eager|
+| Resnet 152 |Image Classification | ImageNet | 214 MB | [.mar](https://torchserve.pytorch.org/mar_files/resnet-152-batch_v2.mar) | [kitten.jpg](../examples/image_classifier/kitten.jpg) |Eager|
+| Faster RCNN | Object Detection | COCO | 148 MB | [.mar](https://torchserve.pytorch.org/mar_files/fastrcnn.mar) | [persons.jpg](../examples/object_detector/persons.jpg) |Eager|
+| MASK RCNN | Object Detection | COCO | 158 MB | [.mar](https://torchserve.pytorch.org/mar_files/maskrcnn.mar) | [persons.jpg](../examples/object_detector/persons.jpg) |Eager|
+| Text classifier | Text Classification | AG_NEWS | 169 MB | [.mar](https://torchserve.pytorch.org/mar_files/my_text_classifier_v4.mar) | [sample_text.txt](../examples/text_classification/sample_text.txt) |Eager|
+| FCN ResNet 101 | Image Segmentation | COCO | 193 MB | [.mar](https://torchserve.pytorch.org/mar_files/fcn_resnet_101.mar) | [persons.jpg](../examples/image_segmenter/persons.jpg) |Eager|
+| DeepLabV3 ResNet 101 | Image Segmentation | COCO | 217 MB | [.mar](https://torchserve.pytorch.org/mar_files/deeplabv3_resnet_101_eager.mar) | [persons.jpg](https://github.com/pytorch/serve/blob/master/examples/image_segmenter/persons.jpg) |Eager|
+| AlexNet Scripted | Image Classification | ImageNet | 216 MB | [.mar](https://torchserve.pytorch.org/mar_files/alexnet_scripted.mar) | [kitten.jpg](../examples/image_classifier/kitten.jpg) |Torchscripted |
+| Densenet161 Scripted| Image Classification | ImageNet | 105 MB | [.mar](https://torchserve.pytorch.org/mar_files/densenet161_scripted.mar) | [kitten.jpg](../examples/image_classifier/kitten.jpg) |Torchscripted |
+| Resnet18 Scripted| Image Classification | ImageNet | 42 MB | [.mar](https://torchserve.pytorch.org/mar_files/resnet-18_scripted.mar) | [kitten.jpg](../examples/image_classifier/kitten.jpg) |Torchscripted |
+| VGG16 Scripted| Image Classification | ImageNet | 489 MB | [.mar](https://torchserve.pytorch.org/mar_files/vgg16_scripted.mar) | [kitten.jpg](../examples/image_classifier/kitten.jpg) |Torchscripted |
+| Squeezenet 1_1 Scripted | Image Classification | ImageNet | 4.4 MB | [.mar](https://torchserve.pytorch.org/mar_files/squeezenet1_1_scripted.mar) | [kitten.jpg](../examples/image_classifier/kitten.jpg) |Torchscripted |
+| MNIST digit classifier Scripted | Image Classification | MNIST | 4.3 MB | [.mar](https://torchserve.pytorch.org/mar_files/mnist_scripted_v2.mar) | [0.png](../examples/image_classifier/mnist/test_data/0.png) |Torchscripted |
+| Resnet 152 Scripted |Image Classification | ImageNet | 215 MB | [.mar](https://torchserve.pytorch.org/mar_files/resnet-152-scripted_v2.mar) | [kitten.jpg](../examples/image_classifier/kitten.jpg) |Torchscripted |
+| Text classifier Scripted | Text Classification | AG_NEWS | 169 MB | [.mar](https://torchserve.pytorch.org/mar_files/my_text_classifier_scripted_v3.mar) | [sample_text.txt](../examples/text_classification/sample_text.txt) |Torchscripted |
+| FCN ResNet 101 Scripted | Image Segmentation | COCO | 193 MB | [.mar](https://torchserve.pytorch.org/mar_files/fcn_resnet_101_scripted.mar) | [persons.jpg](../examples/image_segmenter/persons.jpg) |Torchscripted |
+| DeepLabV3 ResNet 101 Scripted | Image Segmentation | COCO | 217 MB | [.mar](https://torchserve.pytorch.org/mar_files/deeplabv3_resnet_101_scripted.mar) | [persons.jpg](https://github.com/pytorch/serve/blob/master/examples/image_segmenter/persons.jpg) |Torchscripted |
+
+Refer [example](../examples) for more details on above models.

python/examples/detection/README.md

@@ -4,11 +4,11 @@
 
 ### Introduction
 
-PaddleDetection flying paddle target detection development kit is designed to help developers complete the whole development process of detection model formation, training, optimization and deployment faster and better. For details, see [Github](https://github.com/PaddlePaddle/PaddleDetection/tree/master/dygraph)
+PaddleDetection flying paddle target detection development kit is designed to help developers complete the whole development process of detection model formation, training, optimization and deployment faster and better. For details, see [Github](https://github.com/PaddlePaddle/PaddleDetection/tree/master)
 
 This article mainly introduces the deployment of Paddle Detection's dynamic graph model on Serving.
 
-Paddle Detection provides a large number of [Model Zoo](https://github.com/PaddlePaddle/PaddleDetection/blob/master/dygraph/docs/MODEL_ZOO_cn.md), these model libraries can be used in Paddle Serving with export tools Model. For the export tutorial, please refer to [Paddle Detection Export Model Tutorial (Simplified Chinese)](https://github.com/PaddlePaddle/PaddleDetection/blob/master/dygraph/deploy/EXPORT_MODEL.md).
+Paddle Detection provides a large number of [Model Zoo](https://github.com/PaddlePaddle/PaddleDetection/blob/master/docs/MODEL_ZOO_cn.md), these model libraries can be used in Paddle Serving with export tools Model. For the export tutorial, please refer to [Paddle Detection Export Model Tutorial (Simplified Chinese)](https://github.com/PaddlePaddle/PaddleDetection/blob/master/deploy/EXPORT_MODEL.md).
 
 ### Serving example
 Several examples of PaddleDetection models used in Serving are given in this folder

python/examples/detection/README_CN.md

@@ -4,13 +4,13 @@
 
 ### 简介
 
-PaddleDetection飞桨目标检测开发套件，旨在帮助开发者更快更好地完成检测模型的组建、训练、优化及部署等全开发流程。详情参见[Github](https://github.com/PaddlePaddle/PaddleDetection/tree/master/dygraph)
+PaddleDetection飞桨目标检测开发套件，旨在帮助开发者更快更好地完成检测模型的组建、训练、优化及部署等全开发流程。详情参见[Github](https://github.com/PaddlePaddle/PaddleDetection/tree/master)
 
 本文主要是介绍Paddle Detection的动态图模型在Serving上的部署。
 
 ### 导出模型
 
-Paddle Detection提供了大量的[模型库](https://github.com/PaddlePaddle/PaddleDetection/blob/master/dygraph/docs/MODEL_ZOO_cn.md), 这些模型库配合导出工具都可以得到可以用于Paddle Serving的模型。导出教程参见[Paddle Detection模型导出教程](https://github.com/PaddlePaddle/PaddleDetection/blob/master/dygraph/deploy/EXPORT_MODEL.md)。
+Paddle Detection提供了大量的[模型库](https://github.com/PaddlePaddle/PaddleDetection/blob/master/docs/MODEL_ZOO_cn.md), 这些模型库配合导出工具都可以得到可以用于Paddle Serving的模型。导出教程参见[Paddle Detection模型导出教程](https://github.com/PaddlePaddle/PaddleDetection/blob/master/deploy/EXPORT_MODEL.md)。
 
 ### Serving示例
 本文件夹下给出了多个PaddleDetection模型用于Serving的范例

python/examples/pipeline/PaddleDetection/ppyolo_mbv3/README_CN.md

+# PPYOLO model on Pipeline Paddle Serving
+
+(简体中文|[English](./README_CN.md))
+
+### 获取模型
+```
+wget --no-check-certificate https://paddle-serving.bj.bcebos.com/pddet_demo/2.0/ppyolo_mbv3_large_coco.tar
+```
+
+### 启动服务
+```
+tar xf ppyolo_mbv3_large_coco.tar
+python3 web_service.py
+```
+
+### 执行预测
+```
+python3 pipeline_http_client.py
+```

python/examples/pipeline/PaddleDetection/yolov3/README_CN.md

+# YOLOv3 model on Pipeline Paddle Serving
+
+(简体中文|[English](./README.md))
+
+### 获取模型
+```
+wget --no-check-certificate https://paddle-serving.bj.bcebos.com/pddet_demo/2.0/yolov3_darknet53_270e_coco.tar
+```
+
+### 启动 WebService
+```
+tar xf yolov3_darknet53_270e_coco.tar
+python3 web_service.py
+```
+
+### 执行预测
+```
+python3 pipeline_http_client.py
+```

python/paddle_serving_app/README.md

@@ -67,7 +67,7 @@ Preprocessing for Chinese word segmentation task.
     - words（st ）：Original text input.
     - crf_decode（np.array）：CRF code predicted by model.
 
-  [example](../examples/lac/lac_web_service.py)
+  [example](../examples/lac/lac_http_client.py)
 
 - class SentaReader
 

python/paddle_serving_app/README_CN.md

@@ -60,7 +60,7 @@ paddle_serving_app针对CV和NLP领域的模型任务，提供了多种常见的
     - words（str）：原始文本
     - crf_decode（np.array）：模型预测结果中的CRF编码
 
-  [参考示例](../examples/lac/lac_web_service.py)
+  [参考示例](../examples/lac/lac_http_client.py)
 
 - class SentaReader