[Other] Add detection, segmentation and OCR examples for Ascend deploy. (#983)

* Add Huawei Ascend NPU deploy through PaddleLite CANN

* Add NNAdapter interface for paddlelite

* Modify Huawei Ascend Cmake

* Update way for compiling Huawei Ascend NPU deployment

* remove UseLiteBackend in UseCANN

* Support compile python whlee

* Change names of nnadapter API

* Add nnadapter pybind and remove useless API

* Support Python deployment on Huawei Ascend NPU

* Add models suppor for ascend

* Add PPOCR rec reszie for ascend

* fix conflict for ascend

* Rename CANN to Ascend

* Rename CANN to Ascend

* Improve ascend

* fix ascend bug

* improve ascend docs

* improve ascend docs

* improve ascend docs

* Improve Ascend

* Improve Ascend

* Move ascend python demo

* Imporve ascend

* Improve ascend

* Improve ascend

* Improve ascend

* Improve ascend

* Imporve ascend

* Imporve ascend

* Improve ascend

* acc eval script

* acc eval

* remove acc_eval from branch huawei

* Add detection and segmentation examples for Ascend deployment

* Add detection and segmentation examples for Ascend deployment

* Add PPOCR example for ascend deploy

* Imporve paddle lite compiliation

* Add FlyCV doc

* Add FlyCV doc

* Add FlyCV doc

* Imporve Ascend docs

* Imporve Ascend docs

docs/en/faq/boost_cv_by_flycv.md

@@ -0,0 +1,66 @@
+[简体中文](../../cn/faq/boost_cv_by_flycv.md) | English
+
+
+# Accelerate end-to-end inference performance using FlyCV
+
+[FlyCV](https://github.com/PaddlePaddle/FlyCV) is a high performance computer image processing library, providing better performance than other image processing libraries, especially in the ARM architecture.
+FastDeploy is now integrated with FlyCV, allowing users to use FlyCV on supported hardware platforms to accelerate model end-to-end inference performance.
+
+## Supported OS and Architectures
+
+| OS | Architectures |
+| :-----------| :--------   |
+|   Android     |  armeabi-v7a, arm64-v8a |  
+|   Linux       |  aarch64, armhf, x86_64|  
+
+
+## Usage
+To use FlyCV, you first need to turn on the FlyCV compile option at compile time, and then add a new line of code to turn it on.
+This article uses Linux as an example to show how to enable the FlyCV compile option, and then add a new line of code to use FlyCV during deployment.
+
+You can turn on the FlyCV compile option when compiling the FastDeploy library as follows.
+```bash
+# When compiling C++ libraries
+-DENABLE_VISION=ON
+
+#  When compiling Python libraries
+export ENABLE_FLYCV=ON
+```
+
+You can enable FlyCV by adding a new line of code to the deployment code as follows.
+```bash
+# C++ code
+fastdeploy::vision::EnableFlyCV();
+# Other..(e.g. With Huawei Ascend)
+fastdeploy::RuntimeOption option;
+option.UseAscend();
+...
+
+
+# Python code
+fastdeploy.vision.enable_flycv()
+# Other..(e.g. With Huawei Ascend)
+runtime_option = build_option()
+option.use_ascend()
+...
+```
+
+## Some Platforms FlyCV End-to-End Inference Performance
+
+KunPeng 920 CPU + Atlas 300I Pro.
+| Model | OpenCV E2E Performance(ms) | FlyCV E2E Performance(ms) |  
+| :-----------| :--------   | :--------   |
+|   ResNet50     | 2.78  | 1.63  |  
+|   PP-LCNetV2   |  2.50 |  1.39   |  
+|   YOLOv7       |  27.00 | 21.36    |  
+|   PP_HumanSegV2_Lite   | 2.76 |  2.10   |  
+
+
+Rockchip RV1126.
+
+| Model | OpenCV E2E Performance(ms) | FlyCV E2E Performance(ms) |  
+| :-----------| :--------   | :--------   |
+|   ResNet50     | 9.23  | 6.01  |  
+|   mobilenetv1_ssld_量化模型   |  9.23 |  6.01   |  
+|   yolov5s_量化模型       |  28.33 | 14.25    |  
+|   PP_LiteSeg_量化模型  | 132.25 |  60.31   |  

docs/en/faq/use_sdk_on_ascend.md

@@ -1,4 +1,4 @@
-[简体中文](../../cn/faq/use_sdk_on_linux.md) | English
+[简体中文](../../cn/faq/use_sdk_on_ascend.md) | English
 
 
 # # Linux deployment with C++ on Huawei Ascend