02_create_clothdataset.py 文件源码

def convert(inputs):
    imname = inputs['original_filename']
    image = inputs['image']
    labels = inputs['labels']
    label_vis = inputs['label_vis']
    results = []
    segmentation = labels[:, :, 0]
    norm_factor = float(crop) / max(image.shape[:2])
    image = scipy.misc.imresize(image, norm_factor, interp='bilinear')
    segmentation = scipy.misc.imresize(segmentation, norm_factor, interp='nearest')
    if image.shape[0] < crop:
        # Pad height.
        image = pad_height(image, crop)
        segmentation = pad_height(segmentation, crop)
    if image.shape[1] < crop:
        image = pad_width(image, crop)
        segmentation = pad_width(segmentation, crop)
    labels = np.dstack([segmentation] * 3)
    label_vis = apply_colormap(segmentation, vmax=21, vmin=0, cmap=CMAP)[:, :, :3]
    results.append([imname, image * (labels != 0), labels, label_vis])
    # Swapped version.
    imname = path.splitext(imname)[0] + '_swapped' + path.splitext(imname)[1]
    image = image[:, ::-1]
    segmentation = segmentation[:, ::-1]
    segmentation = lrswap_regions(segmentation)
    labels = np.dstack([segmentation] * 3)
    label_vis = apply_colormap(segmentation, vmax=21, vmin=0, cmap=CMAP)[:, :, :3]
    results.append([imname, image * (labels != 0), labels, label_vis])
    return results