python读取的复杂Matlab struct mat文件
python读取的复杂Matlab struct mat文件
提问于 2018-02-25 14:15:42
我知道mat文件的版本问题，它们对应于python中不同的加载模块，即scipy.io和h5py。我还搜索了很多类似的问题，比如scipy.io.loadmat nested structures (i.e. dictionaries)和How to preserve Matlab struct when accessing in python?。但是当涉及到更复杂的mat文件时，它们都失败了。我的anno_bbox.mat文件结构如下：
前两个级别：
在大小中：
在机舱里：
在hoi bboxhuman中：
当我使用spio.loadmat('anno_bbox.mat', struct_as_record=False, squeeze_me=True)时，它只能以字典的形式获取第一级信息。
>>> anno_bbox.keys()
dict_keys(['__header__', '__version__', '__globals__', 'bbox_test',
'bbox_train', 'list_action'])
>>> bbox_test = anno_bbox['bbox_test']
>>> bbox_test.keys()
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
AttributeError: 'numpy.ndarray' object has no attribute 'keys'
>>> bbox_test
array([<scipy.io.matlab.mio5_params.mat_struct object at 0x7fa8660ab128>,
<scipy.io.matlab.mio5_params.mat_struct object at 0x7fa8660ab2b0>,
<scipy.io.matlab.mio5_params.mat_struct object at 0x7fa8660ab710>,
...,
<scipy.io.matlab.mio5_params.mat_struct object at 0x7fa8622ec4a8>,
<scipy.io.matlab.mio5_params.mat_struct object at 0x7fa8622ecb00>,
<scipy.io.matlab.mio5_params.mat_struct object at 0x7fa8622f1198>], dtype=object)我不知道下一步该怎么办。这对我来说太复杂了。该文件可在anno_bbox.mat (8.7MB)上找到
回答 2
Stack Overflow用户
回答已采纳
发布于 2018-02-25 17:10:19
我得到(在这种情况下，使用共享文件是一个好主意)：
使用以下选项加载：
data = io.loadmat('../Downloads/anno_bbox.mat')我得到了：
In [96]: data['bbox_test'].dtype
Out[96]: dtype([('filename', 'O'), ('size', 'O'), ('hoi', 'O')])
In [97]: data['bbox_test'].shape
Out[97]: (1, 9658)我本可以指派bbox_test=data['bbox_test']的。这个变量有9658条记录，有三个字段，每个字段都有对象数据类型。
所以有一个文件名(一个嵌入在1元素数组中的字符串)
In [101]: data['bbox_test'][0,0]['filename']
Out[101]: array(['HICO_test2015_00000001.jpg'], dtype='<U26')size有3个字段，3个数字嵌入到数组中(2d matlab矩阵)：
In [102]: data['bbox_test'][0,0]['size']
Out[102]:
array([[(array([[640]], dtype=uint16), array([[427]], dtype=uint16), array([[3]], dtype=uint8))]],
dtype=[('width', 'O'), ('height', 'O'), ('depth', 'O')])
In [112]: data['bbox_test'][0,0]['size'][0,0].item()
Out[112]:
(array([[640]], dtype=uint16),
array([[427]], dtype=uint16),
array([[3]], dtype=uint8))hoi更加复杂：
In [103]: data['bbox_test'][0,0]['hoi']
Out[103]:
array([[(array([[246]], dtype=uint8), array([[(array([[320]], dtype=uint16), array([[359]], dtype=uint16), array([[306]], dtype=uint16), array([[349]], dtype=uint16)),...
dtype=[('id', 'O'), ('bboxhuman', 'O'), ('bboxobject', 'O'), ('connection', 'O'), ('invis', 'O')])
In [126]: data['bbox_test'][0,1]['hoi']['id']
Out[126]:
array([[array([[132]], dtype=uint8), array([[140]], dtype=uint8),
array([[144]], dtype=uint8)]], dtype=object)
In [130]: data['bbox_test'][0,1]['hoi']['bboxhuman'][0,0]
Out[130]:
array([[(array([[226]], dtype=uint8), array([[340]], dtype=uint16), array([[18]], dtype=uint8), array([[210]], dtype=uint8))]],
dtype=[('x1', 'O'), ('x2', 'O'), ('y1', 'O'), ('y2', 'O')])因此，您在MATLAB结构中显示的数据都在那里，在数组(通常是2d (1,1)形状)、对象数据类型或多个字段的嵌套结构中。
返回并使用squeeze_me加载，我得到了一个更简单的结果：
In [133]: data['bbox_test'][1]['hoi']['bboxhuman']
Out[133]:
array([array((226, 340, 18, 210),
dtype=[('x1', 'O'), ('x2', 'O'), ('y1', 'O'), ('y2', 'O')]),
array((230, 356, 19, 212),
dtype=[('x1', 'O'), ('x2', 'O'), ('y1', 'O'), ('y2', 'O')]),
array((234, 342, 13, 202),
dtype=[('x1', 'O'), ('x2', 'O'), ('y1', 'O'), ('y2', 'O')])],
dtype=object)有了struct_as_record='False'，我得到了
In [136]: data['bbox_test'][1]
Out[136]: <scipy.io.matlab.mio5_params.mat_struct at 0x7f90841e9748>查看这个字段的属性，我发现我可以通过属性名称访问‘rec’：
In [137]: rec = data['bbox_test'][1]
In [138]: rec.filename
Out[138]: 'HICO_test2015_00000002.jpg'
In [139]: rec.size
Out[139]: <scipy.io.matlab.mio5_params.mat_struct at 0x7f90841e9b38>
In [141]: rec.size.width
Out[141]: 640
In [142]: rec.hoi
Out[142]:
array([<scipy.io.matlab.mio5_params.mat_struct object at 0x7f90841e9be0>,
<scipy.io.matlab.mio5_params.mat_struct object at 0x7f90841e9e10>,
<scipy.io.matlab.mio5_params.mat_struct object at 0x7f90841ee0b8>],
dtype=object)
In [145]: rec.hoi[1].bboxhuman
Out[145]: <scipy.io.matlab.mio5_params.mat_struct at 0x7f90841e9f98>
In [146]: rec.hoi[1].bboxhuman.x1
Out[146]: 230
In [147]: vars(rec.hoi[1].bboxhuman)
Out[147]:
{'_fieldnames': ['x1', 'x2', 'y1', 'y2'],
'x1': 230,
'x2': 356,
'y1': 19,
'y2': 212}诸若此类。
Stack Overflow用户
发布于 2020-02-24 00:01:06
我已经修改了答案，网址是：https://stackoverflow.com/a/29126361/12899265
from scipy.io import loadmat, matlab
def load_mat(filename):
"""
This function should be called instead of direct scipy.io.loadmat
as it cures the problem of not properly recovering python dictionaries
from mat files. It calls the function check keys to cure all entries
which are still mat-objects
"""
def _check_vars(d):
"""
Checks if entries in dictionary are mat-objects. If yes
todict is called to change them to nested dictionaries
"""
for key in d:
if isinstance(d[key], matlab.mio5_params.mat_struct):
d[key] = _todict(d[key])
elif isinstance(d[key], np.ndarray):
d[key] = _toarray(d[key])
return d
def _todict(matobj):
"""
A recursive function which constructs from matobjects nested dictionaries
"""
d = {}
for strg in matobj._fieldnames:
elem = matobj.__dict__[strg]
if isinstance(elem, matlab.mio5_params.mat_struct):
d[strg] = _todict(elem)
elif isinstance(elem, np.ndarray):
d[strg] = _toarray(elem)
else:
d[strg] = elem
return d
def _toarray(ndarray):
"""
A recursive function which constructs ndarray from cellarrays
(which are loaded as numpy ndarrays), recursing into the elements
if they contain matobjects.
"""
if ndarray.dtype != 'float64':
elem_list = []
for sub_elem in ndarray:
if isinstance(sub_elem, matlab.mio5_params.mat_struct):
elem_list.append(_todict(sub_elem))
elif isinstance(sub_elem, np.ndarray):
elem_list.append(_toarray(sub_elem))
else:
elem_list.append(sub_elem)
return np.array(elem_list)
else:
return ndarray
data = loadmat(filename, struct_as_record=False, squeeze_me=True)
return _check_vars(data)如果它是一个有结构的矩阵/单元格，它就会遍历变量，而且不会遍历没有结构的矩阵，这也让它更快。
页面原文内容由Stack Overflow提供。腾讯云小微IT领域专用引擎提供翻译支持
原文链接：
https://stackoverflow.com/questions/48970785
复制相关文章
相似问题
腾讯云开发者
Copyright © 2013 - 2026 Tencent Cloud. All Rights Reserved. 腾讯云 版权所有
深圳市腾讯计算机系统有限公司 ICP备案/许可证号：粤B2-20090059 
粤公网安备44030502008569号
腾讯云计算（北京）有限责任公司 京ICP证150476号 | 京ICP备11018762号