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/ncnn/tools/pnnx/tests/test_nn_AdaptiveMaxPool3d.py

@@ -0,0 +1,59 @@
+# Tencent is pleased to support the open source community by making ncnn available.
+#
+# Copyright (C) 2021 THL A29 Limited, a Tencent company. All rights reserved.
+#
+# Licensed under the BSD 3-Clause License (the "License"); you may not use this file except
+# in compliance with the License. You may obtain a copy of the License at
+#
+# https://opensource.org/licenses/BSD-3-Clause
+#
+# Unless required by applicable law or agreed to in writing, software distributed
+# under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR
+# CONDITIONS OF ANY KIND, either express or implied. See the License for the
+# specific language governing permissions and limitations under the License.
+
+import torch
+import torch.nn as nn
+import torch.nn.functional as F
+
+class Model(nn.Module):
+    def __init__(self):
+        super(Model, self).__init__()
+
+        #self.pool_0 = nn.AdaptiveAvgPool3d(output_size=(7,6,5), return_indices=True)
+        self.pool_0 = nn.AdaptiveAvgPool3d(output_size=(7,6,5))
+        self.pool_1 = nn.AdaptiveAvgPool3d(output_size=1)
+
+    def forward(self, x):
+        x = self.pool_0(x)
+        x = self.pool_1(x)
+        return x
+
+def test():
+    net = Model()
+    net.eval()
+
+    torch.manual_seed(0)
+    x = torch.rand(1, 128, 13, 13, 13)
+
+    a = net(x)
+
+    # export torchscript
+    mod = torch.jit.trace(net, x)
+    mod.save("test_nn_AdaptiveAvgPool3d.pt")
+
+    # torchscript to pnnx
+    import os
+    os.system("../src/pnnx test_nn_AdaptiveAvgPool3d.pt inputshape=[1,128,13,13,13]")
+
+    # pnnx inference
+    import test_nn_AdaptiveAvgPool3d_pnnx
+    b = test_nn_AdaptiveAvgPool3d_pnnx.test_inference()
+
+    return torch.equal(a, b)
+
+if __name__ == "__main__":
+    if test():
+        exit(0)
+    else:
+        exit(1)