[Doc] Add PicoDet & PaddleClas Android demo docs

docs/cn/build_and_install/android.md

@@ -102,3 +102,4 @@ make install
 如何使用FastDeploy Android C++ SDK 请参考使用案例文档：  
 - [图像分类Android使用文档](../../../examples/vision/classification/paddleclas/android/README.md)  
 - [目标检测Android使用文档](../../../examples/vision/detection/paddledetection/android/README.md)  
+- [在 Android 通过 JNI 中使用 FastDeploy C++ SDK](../../../../../docs/cn/faq/use_cpp_sdk_on_android.md)

docs/cn/faq/use_cpp_sdk_on_android.md

@@ -0,0 +1,231 @@
+# 在 Android 中通过 JNI 使用 FastDeploy C++ SDK  
+本文档将以PicoDet为例，讲解如何通过JNI，将FastDeploy中的模型封装到Android中进行调用。阅读本文档，您至少需要了解C++、Java、JNI以及Android的基础知识。如果您主要关注如何在Java层如何调用FastDeploy的API，则可以不阅读本文档。
+
+## 目录  
+- [新建Java类并定义native API](#Java)  
+- [Android Studio 生成JNI函数定义](#JNI)  
+- [在C++层实现JNI函数](#CPP)  
+- [编写CMakeLists.txt及配置build.gradle](#CMakeAndGradle)  
+- [更多FastDeploy Android 使用案例](#Examples)
+
+## 新建Java类并定义native API  
+<div id="Java"></div>
+
+```java  
+public class PicoDet {
+    protected long mNativeModelContext = 0; // Context from native.
+    protected boolean mInitialized = false;
+    // ...
+    // Bind predictor from native context.
+    private static native long bindNative(String modelFile,
+                                          String paramsFile,
+                                          String configFile,
+                                          int cpuNumThread,
+                                          boolean enableLiteFp16,
+                                          int litePowerMode,
+                                          String liteOptimizedModelDir,
+                                          boolean enableRecordTimeOfRuntime,
+                                          String labelFile);
+
+    // Call prediction from native context.
+    private static native long predictNative(long nativeModelContext,
+                                             Bitmap ARGB8888Bitmap,
+                                             boolean saved,
+                                             String savedImagePath,
+                                             float scoreThreshold,
+                                             boolean rendering);
+
+    // Release buffers allocated in native context.
+    private static native boolean releaseNative(long nativeModelContext);
+
+    // Initializes at the beginning.
+    static {
+        FastDeployInitializer.init();
+    }
+}
+```
+这些被标记为native的接口是需要通过JNI的方式实现，并在Java层供PicoDet类调用。完整的PicoDet Java代码请参考 [PicoDet.java](../../../examples/vision/detection/paddledetection/android/app/src/main/java/com/baidu/paddle/fastdeploy/vision/detection/PicoDet.java) 。各个函数说明如下：  
+- `bindNative`: C++层初始化模型资源，如果成功初始化，则返回指向该模型的指针(long类型)，否则返回0指针  
+- `predictNative`: 通过已经初始化好的模型指针，在C++层执行预测代码，如果预测成功则返回指向预测结果的指针，否则返回0指针。注意，该结果指针在当次预测使用完之后需要释放，具体操作请参考 [PicoDet.java](../../../examples/vision/detection/paddledetection/android/app/src/main/java/com/baidu/paddle/fastdeploy/vision/detection/PicoDet.java) 中的predict函数。  
+- `releaseNative`: 根据传入的模型指针，在C++层释放模型资源。
+
+## Android Studio 生成JNI函数定义  
+<div id="JNI"></div>
+
+Android Studio 生成 JNI 函数定义: 鼠标停留在Java中定义的native函数上，Android Studio 便会提示是否要创建JNI函数定义；这里，我们把JNI函数定义创建在一个事先创建好的c++文件`picodet_jni.cc`上;
+
+- 使用Android Studio创建JNI函数定义：
+![](https://user-images.githubusercontent.com/31974251/197341065-cdf8f626-4bb1-4a57-8d7a-80b382fe994e.png)  
+
+- 将JNI函数定义创建在picodet_jni.cc上：
+![](https://user-images.githubusercontent.com/31974251/197341190-b887dec5-fa75-43c9-9ab3-7ead50c0eb45.png)
+
+- 创建的JNI函数定义如下：  
+![](https://user-images.githubusercontent.com/31974251/197341274-e9671bac-9e77-4043-a870-9d5db914586b.png)
+
+其他native函数对应的JNI函数定义的创建和此流程一样。  
+
+## 在C++层实现JNI函数  
+<div id="CPP"></div>
+
+以下为PicoDet JNI层实现的示例，相关的辅助函数不在此处赘述，完整的C++代码请参考 [android/app/src/main/cpp](../../../examples/vision/detection/paddledetection/android/app/src/main/cpp/).
+```C++
+#include <jni.h>  // NOLINT
+#include "fastdeploy_jni.h"  // NOLINT
+
+#ifdef __cplusplus
+extern "C" {
+#endif
+
+// 绑定C++层的模型
+JNIEXPORT jlong JNICALL
+Java_com_baidu_paddle_fastdeploy_vision_detection_PicoDet_bindNative(
+    JNIEnv *env, jclass clazz, jstring model_file, jstring params_file,
+    jstring config_file, jint cpu_num_thread, jboolean enable_lite_fp16,
+    jint lite_power_mode, jstring lite_optimized_model_dir,
+    jboolean enable_record_time_of_runtime, jstring label_file) {
+  std::string c_model_file = fastdeploy::jni::ConvertTo<std::string>(env, model_file);
+  std::string c_params_file = fastdeploy::jni::ConvertTo<std::string>(env, params_file);
+  std::string c_config_file = astdeploy::jni::ConvertTo<std::string>(env, config_file);
+  std::string c_label_file = fastdeploy::jni::ConvertTo<std::string>(env, label_file);
+  std::string c_lite_optimized_model_dir = fastdeploy::jni::ConvertTo<std::string>(env, lite_optimized_model_dir);
+  auto c_cpu_num_thread = static_cast<int>(cpu_num_thread);
+  auto c_enable_lite_fp16 = static_cast<bool>(enable_lite_fp16);
+  auto c_lite_power_mode = static_cast<fastdeploy::LitePowerMode>(lite_power_mode);
+  fastdeploy::RuntimeOption c_option;
+  c_option.UseCpu();
+  c_option.UseLiteBackend();
+  c_option.SetCpuThreadNum(c_cpu_num_thread);
+  c_option.SetLitePowerMode(c_lite_power_mode);
+  c_option.SetLiteOptimizedModelDir(c_lite_optimized_model_dir);
+  if (c_enable_lite_fp16) {
+    c_option.EnableLiteFP16();
+  }
+  // 如果您实现的是其他模型，比如PPYOLOE，请注意修改此处绑定的C++类型
+  auto c_model_ptr = new fastdeploy::vision::detection::PicoDet(
+      c_model_file, c_params_file, c_config_file, c_option);
+  // Enable record Runtime time costs.
+  if (enable_record_time_of_runtime) {
+    c_model_ptr->EnableRecordTimeOfRuntime();
+  }
+  // Load detection labels if label path is not empty.
+  if ((!fastdeploy::jni::AssetsLoaderUtils::IsDetectionLabelsLoaded()) &&
+      (!c_label_file.empty())) {
+    fastdeploy::jni::AssetsLoaderUtils::LoadDetectionLabels(c_label_file);
+  }
+  // WARN: need to release manually in Java !
+  return reinterpret_cast<jlong>(c_model_ptr);  // native model context
+}
+
+// 通过传入的模型指针在C++层进行预测
+JNIEXPORT jlong JNICALL
+Java_com_baidu_paddle_fastdeploy_vision_detection_PicoDet_predictNative(
+    JNIEnv *env, jclass clazz, jlong native_model_context,
+    jobject argb8888_bitmap, jboolean saved, jstring saved_image_path,
+    jfloat score_threshold, jboolean rendering) {
+  if (native_model_context == 0) {
+    return 0;
+  }
+  cv::Mat c_bgr;
+  if (!fastdeploy::jni::ARGB888Bitmap2BGR(env, argb8888_bitmap, &c_bgr)) {
+    return 0;
+  }
+  auto c_model_ptr = reinterpret_cast<fastdeploy::vision::detection::PicoDet *>(
+      native_model_context);
+  auto c_result_ptr = new fastdeploy::vision::DetectionResult();
+  t = fastdeploy::jni::GetCurrentTime();
+  if (!c_model_ptr->Predict(&c_bgr, c_result_ptr)) {
+    delete c_result_ptr;
+    return 0;
+  }
+  // ...
+  return reinterpret_cast<jlong>(c_result_ptr);  // native result context
+}
+
+// 在C++层释放模型资源
+JNIEXPORT jboolean JNICALL
+Java_com_baidu_paddle_fastdeploy_vision_detection_PicoDet_releaseNative(
+    JNIEnv *env, jclass clazz, jlong native_model_context) {
+  if (native_model_context == 0) {
+    return JNI_FALSE;
+  }
+  auto c_model_ptr = reinterpret_cast<fastdeploy::vision::detection::PicoDet *>(
+      native_model_context);
+  // ...
+  delete c_model_ptr;
+  return JNI_TRUE;
+}
+
+#ifdef __cplusplus
+}
+#endif
+```  
+## 编写CMakeLists.txt及配置build.gradle  
+<div id="CMakeAndGradle"></div>  
+
+实现好的JNI代码，需要被编译成so库，才能被Java调用，为实现该目的，需要在build.gradle中添加JNI项目支持，并编写对应的CMakeLists.txt。  
+- build.gradle中配置NDK、CMake以及Android ABI  
+```java
+android {
+    defaultConfig {
+        // 省略其他配置 ...
+        externalNativeBuild {
+            cmake {
+                arguments '-DANDROID_PLATFORM=android-21', '-DANDROID_STL=c++_shared', "-DANDROID_TOOLCHAIN=clang"
+                abiFilters 'armeabi-v7a', 'arm64-v8a'
+                cppFlags "-std=c++11"
+            }
+        }
+    }
+    // 省略其他配置 ...
+    externalNativeBuild {
+        cmake {
+            path file('src/main/cpp/CMakeLists.txt')
+            version '3.10.2'
+        }
+    }
+    ndkVersion '20.1.5948944'
+}
+```  
+- 编写CMakeLists.txt示例  
+```cmake  
+cmake_minimum_required(VERSION 3.10.2)
+project("fastdeploy_jni")
+
+set(FastDeploy_DIR "${CMAKE_CURRENT_SOURCE_DIR}/../../../libs/fastdeploy-android-0.4.0-shared")
+
+find_package(FastDeploy REQUIRED)
+
+include_directories(${CMAKE_CURRENT_SOURCE_DIR})
+include_directories(${FastDeploy_INCLUDE_DIRS})
+
+add_library(
+        fastdeploy_jni
+        SHARED
+        utils_jni.cc
+        bitmap_jni.cc
+        vision/results_jni.cc
+        vision/visualize_jni.cc
+        vision/detection/picodet_jni.cc
+        vision/classification/paddleclas_model_jni.cc)
+
+find_library(log-lib log)
+
+target_link_libraries(
+        # Specifies the target library.
+        fastdeploy_jni
+        jnigraphics
+        ${FASTDEPLOY_LIBS}
+        GLESv2
+        EGL
+        ${log-lib}
+)
+```
+完整的工程示例，请参考 [android/app/src/main/cpp/CMakelists.txt](../../../examples/vision/detection/paddledetection/android/app/src/main/cpp/) 以及 [android/app/build.gradle](../../../examples/vision/detection/paddledetection/android/app/build.gradle).
+
+## 更多FastDeploy Android 使用案例  
+<div id="Examples"></div>  
+
+更多FastDeploy Android 使用案例请参考以下文档:  
+- [图像分类Android使用文档](../../../examples/vision/classification/paddleclas/android/README.md)  
+- [目标检测Android使用文档](../../../examples/vision/detection/paddledetection/android/README.md)  

docs/cn/faq/use_java_sdk_on_android.md

@@ -0,0 +1,2 @@
+## 在 Android 中使用 FastDeploy Java SDK  
+- TODO