How do i load a .mat dataset in python?
Show Matlab is a really popular platform for scientific computing in the academia. I’ve used it my throughout my engineering degree and chances are, you will come across .mat files for datasets released by the universities. This is a brief post which explains how to load these files using python, the most popular language for machine learning today. The dataI wanted to build a classifier for detecting cars of different models and makes and so the Stanford Cars Dataset appeared to be a great starting point. Coming from the academia, the annotations for the dataset was in the .mat format. You can get the file used in this post here. Loading .mat filesScipy is a really popular python library used for scientific computing and quite naturally, they have a method which lets you read in .mat files. Reading them in is definitely the easy part. You can get it done in one line of code: from scipy.io import loadmat Well, it’s really that simple. But let’s go on and actually try to get the data we need out of this dictionary. Formatting the dataThe loadmat method returns a more familiar data structure, a python dictionary. If we peek into the keys, we’ll see how at home we feel now compared to dealing with a .mat file: annots.keys() Looking at the documentation for this dataset, we’ll get to learn what this is really made of. The README.txt gives us the following information: This file gives documentation for the cars 196 dataset. Our interest is in the 'annotations' variable, as it contains our class labels and bounding boxes. It’s a struct, a data type very familiar to folks coming from a strongly typed language like a flavour of C or java. A little digging into the object gives us some interesting things to work with: type(annots[‘annotations’]),annots[‘annotations’].shape The annotations are stored in a numpy.ndarray format, however the data type for the items inside this array is numpy.void and numpy doesn’t really seem to know the shape of them. The documentation page for the loadmat method tells us how it loads matlab structs into numpy structured arrays.You can access the members of the structs using the keys: annots[‘annotations’][0][0][‘bbox_x1’], annots[‘annotations’][0][0][‘fname’]> (array([[39]], dtype=uint8), array(['00001.jpg'], dtype=' So now that we know how to access the members of the struct, we can iterate through all of them and store them in a list: [item.flat[0] for item in annots[‘annotations’][0][0]]> [39, 116, 569, 375, 14, '00001.jpg'] Here, we can use the flat method to squeeze the value out of the array. Hello PandasNow that we know how to deal with matlab files in python, let’s convert it into a pandas data frame. We can do so easily using a list of lists: data = [[row.flat[0] for row in line] for line in annots[‘annotations’][0]]columns = [‘bbox_x1’, ‘bbox_y1’, ‘bbox_x2’, ‘bbox_y2’, ‘class’, ‘fname’] Finally, familiar territory! The code for this post can be found here. How do you upload a .MAT file in Python?By default, Python is not capable of reading . mat files.. Install scipy. ... . Import the scipy. ... . Parse the . ... . Use Pandas dataframes to work with the data.. How do I open a MATLAB data file in Python?Read Matlab mat Files in Python. Use the scipy.io Module to Read .mat Files in Python.. Use the NumPy Module to Read mat Files in Python.. Use the mat4py Module to Read mat Files in Python.. Use the matlab.engine Module to Read mat Files in Python.. How do I open a .MAT file?How to Open an MAT File. MAT files that are Microsoft Access Shortcut files can be created by dragging a table out of Access and to the desktop or into another folder. Microsoft Access needs to be installed in order to use them. MATLAB from MathWorks can open MAT files that are used by that program.
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