CODEWITHSUNDEEP
tensorflowdeep-learningmnist
user2362956
user2362956

Reputation:

How to prepare my own data for tensorflow?

I install Tensorflow on ubuntu 14.04. I completed MNIST For ML Beginners tutorial. I understood it.

Nor, I try to use my own data. I have train datas as T[1000][10]. Labels are L[2], 1 or 0.

How can I access my data mnist.train.images ?

Upvotes: 8

Views: 3516

Answers (1)

Sung Kim
Sung Kim

Reputation: 8536

In input_data.py, these two functions do the main job.

1. Download

def maybe_download(filename, work_directory):
    """Download the data from Yann's website, unless it's already here."""
    if not os.path.exists(work_directory):
        os.mkdir(work_directory)
    filepath = os.path.join(work_directory, filename)
    if not os.path.exists(filepath):
        filepath, _ = urlretrieve(SOURCE_URL + filename, filepath)
        statinfo = os.stat(filepath)
        print('Succesfully downloaded', filename, statinfo.st_size, 'bytes.')
    return filepath

2 Image to nparray

def extract_images(filename):
    """Extract the images into a 4D uint8 numpy array [index, y, x, depth]."""
    print('Extracting', filename)
    with gzip.open(filename) as bytestream:
        magic = _read32(bytestream)
        if magic != 2051:
            raise ValueError(
                'Invalid magic number %d in MNIST image file: %s' %
                (magic, filename))
        num_images = _read32(bytestream)
        rows = _read32(bytestream)
        cols = _read32(bytestream)
        buf = bytestream.read(rows * cols * num_images)
        data = numpy.frombuffer(buf, dtype=numpy.uint8)
        data = data.reshape(num_images, rows, cols, 1)
        return data

Based on your dataset and location, you can call:

local_file = maybe_download(TRAIN_IMAGES, train_dir)
train_images = extract_images(local_file)

See the full source code at https://github.com/nlintz/TensorFlow-Tutorials/blob/master/input_data.py.

Upvotes: 1

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