OpenCV法兰索引保存和加载不起作用

我正在尝试这个简单的测试，以检查是否可以将预填充的索引存储到文件中，并在以后加载它们。保存的和加载的垫是不同的。此外，knnSearch在匹配过程中抛出SEGFULTS。只有在使用LSHIndexParams（用于二进制特性）时，我才会看到这个问题

在索引保存之前：

%YAML:1.0 mat: !!opencv-matrix rows: 60 cols: 32 dt: u data: [ 10, 157, 16, 137, 81, 214, 178, 39, 45, 5, 74, 1, 172, 30, 38, 196, 144, 59, 131, 33, 84, 152, 17, 223, 39, 52, 10, 67, 18, 6, 141, 206, 11, 91, 50, 141, 119, 86, 190, 48, 45, 76, 94, 167, 236, 30, 183, 228, 246, 125, 151, 231, 197, 144, 49, 236, 39, 125, 138, 131, 14, 63, 61, 223, 15, 95, 35, 135, 119, 30, 190, 168, 45, 232, 91, 231, 204, 94, 159, 228, 246, 93, 147, 231, 197, 144, 125, 238, 38, 60, 143, 135, 14, 55, 57, 213, 10, 149, 16, 129, 81, 214, 178, 39, 45, 5, 74, 1, 172, 30, 6, 196, 144, 27, 131, 33, 22, 152, 17, 207, 39, 52, 10, 67, 18, 6, 141, 206, 124, 236, 196, 30, 137, 161, 70, 207, 210, 179, 169, 24, 99, 225, 105, 158, 9, 226, 104, 26, 58, 111, 142, 51, 184, 134, 85, 124, 243, 123, 210, 8, 10, 0, 16, 129, 81, 214, 176, 3, 45, 5, 66, 1, 140, 30, 38, 196, 128, 25, 131, 1, 4, 152, 17, 196, 7, 20, 26, 67, 2, 4, 13, 206, 244, 172, 157, 122, 137, 237, 69, 206, 210, 179, 161, 24, 115, 241, 73, 27, 9, 226, 104, 26, 58, 111, 218, 51, 217, 131, 85, 124, 240, 121, 198, 34, 197, 36, 157, 103, 128, 46, 103, 184, 112, 162, 43, 88, 215, 115, 9, 123, 17, 68, 104, 106, 49, 212, 217, 10, 237, 166, 101, 20, 192, 115, 2, 32, 252, 188, 189, 118, 137, 124, 85, 158, 179, 247, 166, 24, 223, 247, 75, 59, 129, 214, 236, 26, 56, 103, 251, 32, 219, 251, 85, 63, 194, 113, 198, 114, 196, 64, 157, 39, 1, 78, 38, 8, 40, 178, 35, 8, 214, 115, 73, 27, 144, 84, 104, 98, 96, 212, 217, 8, 197, 178, 65, 20, 0, 115, 3, 34, 11, 91, 50, 141, 119, 86, 191, 48, 13, 76, 94, 167, 236, 30, 183, 228, 246, 125, %YAML:1.0 mat: !!opencv-matrix rows: 60 cols: 32 dt: u data: [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 110, 100, 101, 120, 95, 115, 97, 118, 101, 46, 100, 97, 116, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 241, 1, 0, 0, 0, 0, 0, 0, 152, 169, 51, 241, 97, 127, 0, 0, 152, 169, 51, 241, 97, 127, 0, 0, 0, 0, 0, 0, 98, 101, 102, 111, 114, 101, 95, 105, 110, 100, 101, 120, 95, 115, 97, 118, 101, 46, 100, 97, 116, 0, 0, 0, 0, 0, 0, 0, 64, 0, 0, 0, 0, 0, 0, 0, 176, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 192, 188, 45, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, %YAML:1.0 马特：！！opencv矩阵 行数：60 科尔斯：32 dt:u 数据：[10,157,16,137,81,214,178,39,45,5,74,1172,30,38， 196, 144, 59, 131, 33, 84, 152, 17, 223, 39, 52, 10, 67, 18, 6, 141, 206, 11, 91, 50, 141, 119, 86, 190, 48, 45, 76, 94, 167, 236, 30, 183, 228, 246, 125, 151, 231, 197, 144, 49, 236, 39, 125, 138, 131, 14, 63, 61, 223, 15, 95, 35, 135, 119, 30, 190, 168, 45, 232, 91, 231, 204, 94, 159, 228, 246, 93, 147, 231, 197, 144, 125, 238, 38, 60, 143, 135, 14, 55, 57, 213, 10, 149, 16, 129, 81, 214, 178, 39, 45, 5, 74, 1, 172, 30, 6, 196, 144, 27, 131, 33, 22, 152, 17, 207, 39, 52, 10, 67, 18, 6, 141, 206, 124, 236, 196, 30, 137, 161, 70, 207, 210, 179, 169, 24, 99, 225, 105, 158, 9, 226, 104, 26, 58, 111, 142, 51, 184, 134, 85, 124, 243, 123, 210, 8, 10, 0, 16, 129, 81, 214, 176, 3, 45, 5, 66, 1, 140, 30, 38, 196, 128, 25, 131, 1, 4, 152, 17, 196, 7, 20, 26, 67, 2, 4, 13, 206, 244, 172, 157, 122, 137, 237, 69, 206, 210, 179, 161, 24, 115, 241, 73, 27, 9, 226, 104, 26, 58, 111, 218, 51, 217, 131, 85, 124, 240, 121, 198, 34, 197, 36, 157, 103, 128, 46, 103, 184, 112, 162, 43, 88, 215, 115, 9, 123, 17, 68, 104, 106, 49, 212, 217, 10, 237, 166, 101, 20, 192, 115, 2, 32, 252, 188, 189, 118, 137, 124, 85, 158, 179, 247, 166, 24, 223, 247, 75, 59, 129, 214, 236, 26, 56, 103, 251, 32, 219, 251, 85, 63, 194, 113, 198, 114, 196, 64, 157, 39, 1, 78, 38, 8, 40, 178, 35, 8, 214, 115, 73, 27, 144, 84, 104, 98, 96, 212, 217, 8, 197, 178, 65, 20, 0, 115, 3, 34, 11, 91, 50, 141, 119, 86, 191, 48, 13, 76, 94, 167, 236, 30, 183, 228, 246, 125, 索引保存后：

%YAML:1.0 mat: !!opencv-matrix rows: 60 cols: 32 dt: u data: [ 10, 157, 16, 137, 81, 214, 178, 39, 45, 5, 74, 1, 172, 30, 38, 196, 144, 59, 131, 33, 84, 152, 17, 223, 39, 52, 10, 67, 18, 6, 141, 206, 11, 91, 50, 141, 119, 86, 190, 48, 45, 76, 94, 167, 236, 30, 183, 228, 246, 125, 151, 231, 197, 144, 49, 236, 39, 125, 138, 131, 14, 63, 61, 223, 15, 95, 35, 135, 119, 30, 190, 168, 45, 232, 91, 231, 204, 94, 159, 228, 246, 93, 147, 231, 197, 144, 125, 238, 38, 60, 143, 135, 14, 55, 57, 213, 10, 149, 16, 129, 81, 214, 178, 39, 45, 5, 74, 1, 172, 30, 6, 196, 144, 27, 131, 33, 22, 152, 17, 207, 39, 52, 10, 67, 18, 6, 141, 206, 124, 236, 196, 30, 137, 161, 70, 207, 210, 179, 169, 24, 99, 225, 105, 158, 9, 226, 104, 26, 58, 111, 142, 51, 184, 134, 85, 124, 243, 123, 210, 8, 10, 0, 16, 129, 81, 214, 176, 3, 45, 5, 66, 1, 140, 30, 38, 196, 128, 25, 131, 1, 4, 152, 17, 196, 7, 20, 26, 67, 2, 4, 13, 206, 244, 172, 157, 122, 137, 237, 69, 206, 210, 179, 161, 24, 115, 241, 73, 27, 9, 226, 104, 26, 58, 111, 218, 51, 217, 131, 85, 124, 240, 121, 198, 34, 197, 36, 157, 103, 128, 46, 103, 184, 112, 162, 43, 88, 215, 115, 9, 123, 17, 68, 104, 106, 49, 212, 217, 10, 237, 166, 101, 20, 192, 115, 2, 32, 252, 188, 189, 118, 137, 124, 85, 158, 179, 247, 166, 24, 223, 247, 75, 59, 129, 214, 236, 26, 56, 103, 251, 32, 219, 251, 85, 63, 194, 113, 198, 114, 196, 64, 157, 39, 1, 78, 38, 8, 40, 178, 35, 8, 214, 115, 73, 27, 144, 84, 104, 98, 96, 212, 217, 8, 197, 178, 65, 20, 0, 115, 3, 34, 11, 91, 50, 141, 119, 86, 191, 48, 13, 76, 94, 167, 236, 30, 183, 228, 246, 125, %YAML:1.0 mat: !!opencv-matrix rows: 60 cols: 32 dt: u data: [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 110, 100, 101, 120, 95, 115, 97, 118, 101, 46, 100, 97, 116, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 241, 1, 0, 0, 0, 0, 0, 0, 152, 169, 51, 241, 97, 127, 0, 0, 152, 169, 51, 241, 97, 127, 0, 0, 0, 0, 0, 0, 98, 101, 102, 111, 114, 101, 95, 105, 110, 100, 101, 120, 95, 115, 97, 118, 101, 46, 100, 97, 116, 0, 0, 0, 0, 0, 0, 0, 64, 0, 0, 0, 0, 0, 0, 0, 176, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 192, 188, 45, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, %YAML:1.0 mat:！！opencv矩阵 行数：60 科尔斯：32 dt:u 数据：[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,110,100,101， 120, 95, 115, 97, 118, 101, 46, 100, 97, 116, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 241, 1, 0, 0, 0, 0, 0, 0, 152, 169, 51, 241, 97, 127, 0, 0, 152, 169, 51, 241, 97, 127, 0, 0, 0, 0, 0, 0, 98, 101, 102, 111, 114, 101, 95, 105, 110, 100, 101, 120, 95, 115, 97, 118, 101, 46, 100, 97, 116, 0, 0, 0, 0, 0, 0, 0, 64, 0, 0, 0, 0, 0, 0, 0, 176, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 192, 188, 45, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,

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链接讨论：我只是试图保存并加载一个索引（使用不同的索引参数tho）——为了从文件加载索引，我还必须再次加载数据库描述符（而不仅仅是像你那样给它一个正确大小的空矩阵）。它保存的唯一东西（我想）是索引构建时间。如果您认为这会有所帮助，我可以发布我在代码中所做的事情（但是agian，不同的参数）。