Accessing data in SVHN dataset in python

问题

I tried to extract data from tar.gz file which contains digitStruct.mat file. I used the following code snippet:

train_dataset = h5py.File('./train/digitStruct.mat')

I want to access the bbox and name details from this object itself. for eg:

train_dataset[0]

Should output something like:

{'boxes': [{'height': 219.0,
'label': 1.0,
'left': 246.0,
'top': 77.0,
'width': 81.0},
{'height': 219.0, 'label': 9.0, 'left': 323.0, 'top': 81.0, 'width': 96.0}],
 'filename': '1.png'}

I searched for it and found the some help on this link:

h5py, access data in Datasets in SVHN

But the above link involves creating seperate functions get_box_data(index, hdf5_data) and get_name(index, hdf5_data) to retrieve value for the corresponding index. However, I want access it directly from the variable name train_dataset[index].

回答1:

Ok, I think I found what I mentioned in the comments above. It converts a SVHN HDF5 file in .mat v7.3 format into something simpler to work with. The file name is entered as dsFileName=. (I only had 6 test files to convert, so didn't add an input mechanism.) It takes a file named: yourfilename.mat and converts to yourfilename.h5. The second file is much easier to work with (and smaller and faster!). The new .h5 file has a dataset named digitStruct with the following records on each line:

name: String (file name, eg 1.png)
label: String with digit value (0-9)
left: image bounding box left
top: image bounding box top
width: image bounding box width
height: image bounding box height

Note: This calls code shared on github. URL and Attribution included in the source code below.

import h5py
import numpy as np
import os
import digitStruct
## Note digitStruct.py source found at:
## https://github.com/prijip/Py-Gsvhn-DigitStruct-Reader/blob/master/digitStruct.py

# Main
if __name__ == "__main__":

    dsFileName = 'Stanford/extra/digitStruct.mat'
    print ('Working on',os.path.split(dsFileName))

    print ('Create .h5 called',os.path.splitext(dsFileName)[0]+'.h5')
    h5f = h5py.File(os.path.splitext(dsFileName)[0]+'.h5', 'w')
    print ('Created',os.path.split(h5f.filename))

# Count number of images in digitStruct.mat file [/name] dataset
    mat_f = h5py.File(dsFileName)
    num_img = mat_f['/digitStruct/name'].size
    mat_f.close()

    ds_dtype = np.dtype ( [('name','S16'), ('label','S10'), ('left','f8'),
                            ('top','f8'), ('width','f8'), ('height','f8')] )
    ds_recarray = np.recarray ( (10,) , dtype=ds_dtype )
    ds_table = h5f.create_dataset('digitStruct', (2*num_img,), dtype=ds_dtype, maxshape=(None,) )

    idx_dtype = np.dtype ( [('name','S16'), ('first','i4'), ('length','i4')] )
##    idx_recarray = np.recarray ( (1,) , dtype=idx_dtype )
    idx_table = h5f.create_dataset('idx_digitStruct', (num_img,), dtype=idx_dtype, maxshape=(None,) )

    imgCounter = 0
    lblCounter = 0

    for dsObj in digitStruct.yieldNextDigitStruct(dsFileName):
        if (imgCounter % 1000 == 0) :
               print(dsObj.name)

        if (idx_table.shape[0] < imgCounter ) : # resize idx_table as needed
            idx_table.resize(idx_table.shape[0]+1000, axis=0)

        idx_table[imgCounter,'name'] = dsObj.name
        idx_table[imgCounter,'first'] = lblCounter
        idx_table[imgCounter,'length'] = len(dsObj.bboxList)

        raCounter = 0

        for bbox in dsObj.bboxList:

            ds_recarray[raCounter]['name'] = dsObj.name
            ds_recarray[raCounter]['label'] = bbox.label
            ds_recarray[raCounter]['left'] = bbox.left
            ds_recarray[raCounter]['top'] = bbox.top
            ds_recarray[raCounter]['width'] = bbox.width
            ds_recarray[raCounter]['height'] = bbox.height
            raCounter += 1
            lblCounter += 1

        if (ds_table.shape[0] < lblCounter ) :   # resize ds_table as needed
            ds_table.resize(ds_table.shape[0]+1000, axis=0)
        ds_table[lblCounter-raCounter:lblCounter] = ds_recarray[0:raCounter]

        imgCounter += 1

##        if imgCounter >= 2000:
##            break

    print ('Total images processed:', imgCounter )
    print ('Total labels processed:', lblCounter )

    ds_table.resize(lblCounter, axis=0)
    idx_table.resize(imgCounter, axis=0)

    h5f.close()

来源：https://stackoverflow.com/questions/62161100/accessing-data-in-svhn-dataset-in-python

标签

python

h5py

mat