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/dnn/test/imagenet_cls_test_googlenet.py

@@ -0,0 +1,39 @@
+import numpy as np
+import sys
+import os
+import argparse
+from imagenet_cls_test_alexnet import MeanChannelsFetch, CaffeModel, DnnCaffeModel, ClsAccEvaluation
+try:
+    import caffe
+except ImportError:
+    raise ImportError('Can\'t find Caffe Python module. If you\'ve built it from sources without installation, '
+                      'configure environment variable PYTHONPATH to "git/caffe/python" directory')
+try:
+    import cv2 as cv
+except ImportError:
+    raise ImportError('Can\'t find OpenCV Python module. If you\'ve built it from sources without installation, '
+                      'configure environment variable PYTHONPATH to "opencv_build_dir/lib" directory (with "python3" subdirectory if required)')
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--imgs_dir", help="path to ImageNet validation subset images dir, ILSVRC2012_img_val dir")
+    parser.add_argument("--img_cls_file", help="path to file with classes ids for images, val.txt file from this "
+                                               "archive: http://dl.caffe.berkeleyvision.org/caffe_ilsvrc12.tar.gz")
+    parser.add_argument("--prototxt", help="path to caffe prototxt, download it here: "
+                                        "https://github.com/BVLC/caffe/blob/master/models/bvlc_alexnet/deploy.prototxt")
+    parser.add_argument("--caffemodel", help="path to caffemodel file, download it here: "
+                                             "http://dl.caffe.berkeleyvision.org/bvlc_alexnet.caffemodel")
+    parser.add_argument("--log", help="path to logging file")
+    parser.add_argument("--batch_size", help="size of images in batch", default=500, type=int)
+    parser.add_argument("--frame_size", help="size of input image", default=224, type=int)
+    parser.add_argument("--in_blob", help="name for input blob", default='data')
+    parser.add_argument("--out_blob", help="name for output blob", default='prob')
+    args = parser.parse_args()
+
+    data_fetcher = MeanChannelsFetch(args.frame_size, args.imgs_dir)
+
+    frameworks = [CaffeModel(args.prototxt, args.caffemodel, args.in_blob, args.out_blob),
+                  DnnCaffeModel(args.prototxt, args.caffemodel, '', args.out_blob)]
+
+    acc_eval = ClsAccEvaluation(args.log, args.img_cls_file, args.batch_size)
+    acc_eval.process(frameworks, data_fetcher)