neuro_dataset.py 文件源码

def prepare_n_mnist(filename, is_filter, num_spikes, step_factor=1):
    """Creates images from the specified n mnist recording
    filename: path to the recording
    is_filter: True if median filtering should be applied to the constructed image
    num_spikes: number of unique spikes per image
    step_factor: proportional amount to shift before generating the next image
        1 would result in no overlapping events between images
        0.6 would result in the next image overlapping with 40% of the previous image
    returns: list of images, where each image is a 2d numpy array (height, width)
    """
    td = ev.read_dataset(filename)
    #td.show_td(100)
    td.data = stabilize(td)
    td.data = td.extract_roi([3, 3], [28, 28], True)
    images = make_td_images(td, num_spikes, step_factor)

    if is_filter:
        images = ndimage.median_filter(images, 3)

    #for image in images:
    #    cv2.imshow('img', image)
    #    cv2.waitKey(70)
    return images