我尝试在本教程中训练街景房号（SVHN）数据（Convolutional Neural Networks） 我用了
scipy.io.loadmat
但它不起作用，并给我这个错误::
TypeError：预期字符串，得到{'标题'：b'MATLAB 5.0 MAT文件，平台：GLNXA64，创建时间：2011年12月5日21:09:26'，'版本'：'1.0'，'全局'：[]，'X'：数组（[[[[[84,84,19，...，92,190， 216]， [30,76,54，......，78,188,217]， [38,59,110，...，101,191,212]]，
[[ 15, 86, 20, ..., 94, 205, 221],
[ 23, 73, 52, ..., 82, 203, 222],
[ 19, 66, 111, ..., 105, 206, 217]],
[[ 15, 77, 25, ..., 114, 220, 226],
[ 17, 78, 57, ..., 101, 218, 227],
[ 19, 56, 116, ..., 125, 220, 221]],
...,
[[ 72, 90, 65, ..., 200, 229, 200],
[ 65, 78, 144, ..., 201, 231, 199],
[ 56, 69, 223, ..., 203, 224, 191]],
[[ 82, 88, 78, ..., 192, 229, 193],
[ 77, 77, 148, ..., 193, 229, 188],
[ 57, 67, 218, ..., 195, 224, 182]],
[[ 89, 88, 98, ..., 190, 229, 197],
[ 79, 78, 158, ..., 191, 228, 189],
[ 59, 66, 220, ..., 193, 223, 186]]],
[[[ 28, 85, 21, ..., 92, 183, 204],
[ 39, 77, 53, ..., 78, 182, 205],
[ 35, 61, 110, ..., 103, 186, 202]],
[[ 14, 83, 19, ..., 93, 200, 210],
[ 25, 73, 52, ..., 80, 199, 211],
[ 22, 64, 106, ..., 106, 201, 208]],
[[ 14, 74, 25, ..., 111, 218, 220],
[ 20, 69, 56, ..., 98, 217, 221],
[ 17, 59, 111, ..., 124, 218, 217]],
...,
[[ 40, 89, 63, ..., 181, 227, 201],
[ 39, 82, 137, ..., 180, 228, 199],
[ 50, 64, 208, ..., 184, 223, 193]],
[[ 67, 88, 91, ..., 177, 227, 195],
[ 58, 79, 153, ..., 176, 226, 191],
[ 52, 70, 214, ..., 180, 222, 186]],
[[ 83, 88, 130, ..., 183, 228, 196],
[ 78, 81, 180, ..., 182, 224, 190],
[ 60, 67, 229, ..., 187, 221, 186]]],
[[[ 40, 83, 21, ..., 99, 171, 198],
[ 41, 76, 53, ..., 84, 170, 198],
[ 38, 60, 110, ..., 112, 175, 197]],
[[ 18, 78, 20, ..., 94, 189, 202],
[ 21, 77, 51, ..., 81, 189, 202],
[ 26, 58, 106, ..., 110, 193, 201]],
[[ 16, 61, 22, ..., 107, 213, 212],
[ 17, 50, 52, ..., 94, 213, 211],
[ 23, 54, 106, ..., 123, 215, 210]],
...,
[[ 23, 90, 79, ..., 167, 231, 203],
[ 29, 85, 147, ..., 166, 230, 200],
[ 45, 63, 210, ..., 171, 226, 196]],
[[ 35, 88, 125, ..., 172, 229, 198],
[ 42, 83, 181, ..., 171, 226, 194],
[ 44, 66, 230, ..., 176, 223, 191]],
[[ 72, 85, 178, ..., 185, 227, 195],
[ 69, 82, 218, ..., 184, 223, 190],
[ 53, 70, 254, ..., 189, 220, 187]]],
...,
[[[ 86, 100, 88, ..., 99, 187, 233],
[ 81, 98, 162, ..., 94, 185, 226],
[ 75, 72, 237, ..., 110, 186, 228]],
[[ 87, 98, 89, ..., 96, 204, 230],
[ 82, 94, 163, ..., 91, 202, 224],
[ 71, 76, 238, ..., 109, 199, 225]],
[[ 82, 95, 84, ..., 108, 217, 228],
[ 79, 93, 156, ..., 103, 217, 223],
[ 65, 73, 230, ..., 124, 210, 221]],
...,
[[104, 104, 62, ..., 210, 204, 198],
[104, 104, 142, ..., 207, 200, 196],
[ 87, 86, 227, ..., 204, 195, 190]],
[[104, 102, 67, ..., 206, 196, 184],
[105, 102, 144, ..., 202, 193, 183],
[ 81, 87, 226, ..., 200, 189, 177]],
[[103, 100, 74, ..., 203, 196, 189],
[105, 101, 145, ..., 197, 193, 187],
[ 78, 78, 225, ..., 199, 189, 182]]],
[[[ 84, 103, 88, ..., 94, 186, 231],
[ 86, 104, 164, ..., 91, 184, 226],
[ 64, 79, 240, ..., 103, 185, 228]],
[[ 86, 106, 87, ..., 94, 198, 229],
[ 79, 104, 160, ..., 91, 197, 224],
[ 72, 79, 237, ..., 104, 194, 225]],
[[ 82, 103, 88, ..., 110, 211, 227],
[ 76, 103, 159, ..., 107, 211, 223],
[ 72, 87, 237, ..., 121, 204, 222]],
...,
[[110, 103, 60, ..., 219, 222, 195],
[103, 104, 141, ..., 218, 216, 194],
[ 84, 86, 230, ..., 215, 212, 186]],
[[106, 103, 61, ..., 218, 214, 181],
[105, 103, 141, ..., 215, 209, 181],
[ 85, 87, 228, ..., 212, 205, 173]],
[[106, 105, 65, ..., 212, 208, 186],
[104, 99, 143, ..., 209, 205, 183],
[ 86, 81, 226, ..., 209, 200, 177]]],
[[[ 85, 103, 84, ..., 88, 190, 230],
[ 88, 106, 160, ..., 87, 188, 226],
[ 68, 82, 238, ..., 94, 190, 227]],
[[ 89, 103, 81, ..., 85, 199, 230],
[ 82, 105, 154, ..., 84, 197, 226],
[ 72, 87, 233, ..., 93, 194, 227]],
[[ 85, 104, 87, ..., 105, 208, 229],
[ 79, 106, 158, ..., 103, 208, 225],
[ 67, 91, 238, ..., 114, 201, 226]],
...,
[[111, 113, 63, ..., 217, 232, 190],
[104, 103, 144, ..., 217, 227, 190],
[ 87, 88, 235, ..., 214, 223, 181]],
[[109, 104, 62, ..., 221, 226, 178],
[105, 104, 143, ..., 220, 221, 177],
[ 86, 88, 232, ..., 219, 216, 169]],
[[103, 103, 63, ..., 218, 218, 181],
[106, 98, 145, ..., 217, 213, 178],
[ 79, 80, 231, ..., 218, 209, 171]]]], dtype=uint8), 'y': array([[1],
[9],
[2],
...,
[1],
[6],
[9]], dtype=uint8)} of type 'dict' instead.
我无法理解问题，解决方案是什么。
答案 0 :(得分：0)
该教程使用从文件中读取数据的方法，这种方法通常适用于数据集太大而无法保留在内存中的情况。本教程的这一部分有许多步骤，大部分都在cifar10_input.py中实现，它们通常遵循here步骤。
cifar10_input.py获取从中读取数据的文件名字符串列表。如果没有看到更多的代码，我猜这就是你遇到这个特定错误的原因。
您需要确保SVHN .mat文件具有正确的预期二进制格式（我怀疑是这种情况），然后在cifar10_input.py中为cifar10二进制文件交换该文件名，或者重写cifar10_train.py以使用占位符和feed_dict参数代替读取管道。请记住，需要将SVHN缩小到与cifar10_input.py中的cifar图像相同的大小。另外，对于feed_dict方法，SVHN数据集可能太大。