Function load_samples

data/utils.py:92–137

Args: images_dir: path to the images cells_dir: path to the segmentation cells2labels_dir: path to mapping cells to labels images_names: names of images to load from the images_dir crop_size: the size of the crop of the cell channels: indices of

(images_dir, cells_dir, cells2labels_dir, images_names, crop_size, to_pad=False, channels=None)

def load_samples(images_dir, cells_dir, cells2labels_dir, images_names, crop_size, to_pad=False, channels=None):
    """

    Args:
        images_dir: path to the images
        cells_dir: path to the segmentation
        cells2labels_dir: path to mapping cells to labels
        images_names: names of images to load from the images_dir
        crop_size: the size of the crop of the cell
        channels: indices of channels to load from each image
    Returns:
        Array of CellCrop per cell in the dataset
    """
    images_dir = Path(images_dir)
    cells_dir = Path(cells_dir)
    cells2labels_dir = Path(cells2labels_dir)
    crops = []
    for image_id in images_names:
        image_path = glob.glob(str(images_dir / f"{image_id}.npz")) + \
                     glob.glob(str(images_dir / f"{image_id}.tiff"))
        cells_path = glob.glob(str(cells_dir / f"{image_id}.npz")) + \
                     glob.glob(str(cells_dir / f"{image_id}.tiff"))
        cells2labels_path = glob.glob(str(cells2labels_dir / f"{image_id}.npz")) + \
                            glob.glob(str(cells2labels_dir / f"{image_id}.txt"))
        image, cells, cl2lbl = load_image(image_path=image_path[0],
                                          cells_path=cells_path[0],
                                          cells2labels_path=cells2labels_path[0],
                                          channels=channels,
                                          to_pad=to_pad,
                                          crop_size=crop_size)

        objs = ndimage.find_objects(cells)
        for cell_id, obj in enumerate(objs, 1):
            try:
                slices = create_slices(obj, (crop_size, crop_size), cells.shape)
                label = cl2lbl[cell_id]
                crops.append(
                    CellCrop(cell_id=cell_id,
                             image_id=image_id,
                             label=label,
                             slices=slices,
                             cells=cells,
                             image=image))
            except Exception as e:
                pass
    return np.array(crops)


def load_crops(root_dir,