feat: 切换后端至PaddleOCR-NCNN，切换工程为CMake

1.项目后端整体迁移至PaddleOCR-NCNN算法，已通过基本的兼容性测试
2.工程改为使用CMake组织，后续为了更好地兼容第三方库，不再提供QMake工程
3.重整权利声明文件，重整代码工程，确保最小化侵权风险

Log: 切换后端至PaddleOCR-NCNN，切换工程为CMake
Change-Id: I4d5d2c5d37505a4a24b389b1a4c5d12f17bfa38c

3rdparty/opencv-4.5.4/modules/gapi/doc/00-root.markdown

@@ -0,0 +1,113 @@
+# Graph API {#gapi}
+
+# Introduction {#gapi_root_intro}
+
+OpenCV Graph API (or G-API) is a new OpenCV module targeted to make
+regular image processing fast and portable. These two goals are
+achieved by introducing a new graph-based model of execution.
+
+G-API is a special module in OpenCV -- in contrast with the majority
+of other main modules, this one acts as a framework rather than some
+specific CV algorithm. G-API provides means to define CV operations,
+construct graphs (in form of expressions) using it, and finally
+implement and run the operations for a particular backend.
+
+@note G-API is a new module and now is in active development. It's API
+is volatile at the moment and there may be minor but
+compatibility-breaking changes in the future.
+
+# Contents
+
+G-API documentation is organized into the following chapters:
+
+- @subpage gapi_purposes
+
+  The motivation behind G-API and its goals.
+
+- @subpage gapi_hld
+
+  General overview of G-API architecture and its major internal
+  components.
+
+- @subpage gapi_kernel_api
+
+  Learn how to introduce new operations in G-API and implement it for
+  various backends.
+
+- @subpage gapi_impl
+
+  Low-level implementation details of G-API, for those who want to
+  contribute.
+
+- API Reference: functions and classes
+
+    - @subpage gapi_core
+
+      Core G-API operations - arithmetic, boolean, and other matrix
+      operations;
+
+    - @subpage gapi_imgproc
+
+      Image processing functions: color space conversions, various
+      filters, etc.
+
+# API Example {#gapi_example}
+
+A very basic example of G-API pipeline is shown below:
+
+@include modules/gapi/samples/api_example.cpp
+
+<!-- TODO align this code with text using marks and itemized list -->
+
+G-API is a separate OpenCV module so its header files have to be
+included explicitly. The first four lines of `main()` create and
+initialize OpenCV's standard video capture object, which fetches
+video frames from either an attached camera or a specified file.
+
+G-API pipeline is constructed next. In fact, it is a series of G-API
+operation calls on cv::GMat data. The important aspect of G-API is
+that this code block is just a declaration of actions, but not the
+actions themselves. No processing happens at this point, G-API only
+tracks which operations form pipeline and how it is connected. G-API
+_Data objects_ (here it is cv::GMat) are used to connect operations
+each other. `in` is an _empty_ cv::GMat signalling that it is a
+beginning of computation.
+
+After G-API code is written, it is captured into a call graph with
+instantiation of cv::GComputation object. This object takes
+input/output data references (in this example, `in` and `out`
+cv::GMat objects, respectively) as parameters and reconstructs the
+call graph based on all the data flow between `in` and `out`.
+
+cv::GComputation is a thin object in sense that it just captures which
+operations form up a computation. However, it can be used to execute
+computations -- in the following processing loop, every captured frame (a
+cv::Mat `input_frame`) is passed to cv::GComputation::apply().
+
+![Example pipeline running on sample video 'vtest.avi'](pics/demo.jpg)
+
+cv::GComputation::apply() is a polimorphic method which accepts a
+variadic number of arguments. Since this computation is defined on one
+input, one output, a special overload of cv::GComputation::apply() is
+used to pass input data and get output data.
+
+Internally, cv::GComputation::apply() compiles the captured graph for
+the given input parameters and executes the compiled graph on data
+immediately.
+
+There is a number important concepts can be outlines with this example:
+* Graph declaration and graph execution are distinct steps;
+* Graph is built implicitly from a sequence of G-API expressions;
+* G-API supports function-like calls -- e.g. cv::gapi::resize(), and
+  operators, e.g operator|() which is used to compute bitwise OR;
+* G-API syntax aims to look pure: every operation call within a graph
+  yields a new result, thus forming a directed acyclic graph (DAG);
+* Graph declaration is not bound to any data -- real data objects
+  (cv::Mat) come into picture after the graph is already declared.
+
+<!-- FIXME: The above operator|() link links to MatExpr not GAPI -->
+
+See [tutorials and porting examples](@ref tutorial_table_of_content_gapi)
+to learn more on various G-API features and concepts.
+
+<!-- TODO Add chapter on declaration, compilation, execution -->