extractdata.py

def extract_data(filename, num_images, IMAGE_WIDTH):
    '''
    Extract images by reading the file bytestream. Reshape the read values into a 3D matrix of dimensions [m, h, w], where m 
    is the number of training examples.
    '''
    print('Extracting', filename)
    with gzip.open(filename) as bytestream:
        bytestream.read(16)
        buf = bytestream.read(IMAGE_WIDTH * IMAGE_WIDTH * num_images)
        data = np.frombuffer(buf, dtype=np.uint8).astype(np.float32)
        data = data.reshape(num_images, IMAGE_WIDTH*IMAGE_WIDTH)
        return data

def extract_labels(filename, num_images):
    '''
    Extract label into vector of integer values of dimensions [m, 1], where m is the number of images.
    '''
    print('Extracting', filename)
    with gzip.open(filename) as bytestream:
        bytestream.read(8)
        buf = bytestream.read(1 * num_images)
        labels = np.frombuffer(buf, dtype=np.uint8).astype(np.int64)
    return labels