예제 #1
0
def generate_chunks(meta, img, offset, mip):
    shape = Vec(*img.shape)[:3]
    offset = Vec(*offset)[:3]

    bounds = Bbox(offset, shape + offset)

    alignment_check = bounds.round_to_chunk_size(meta.chunk_size(mip),
                                                 meta.voxel_offset(mip))

    if not np.all(alignment_check.minpt == bounds.minpt):
        raise AlignmentError("""
      Only chunk aligned writes are supported by this function. 

      Got:             {}
      Volume Offset:   {} 
      Nearest Aligned: {}
    """.format(bounds, meta.voxel_offset(mip), alignment_check))

    bounds = Bbox.clamp(bounds, meta.bounds(mip))

    img_offset = bounds.minpt - offset
    img_end = Vec.clamp(bounds.size3() + img_offset, Vec(0, 0, 0), shape)

    for startpt in xyzrange(img_offset, img_end, meta.chunk_size(mip)):
        startpt = startpt.clone()
        endpt = min2(startpt + meta.chunk_size(mip), shape)
        spt = (startpt + bounds.minpt).astype(int)
        ept = (endpt + bounds.minpt).astype(int)
        yield (startpt, endpt, spt, ept)
예제 #2
0
파일: tx.py 프로젝트: ZettaAI/cloud-volume
def generate_chunks(meta, img, offset, mip):
    shape = Vec(*img.shape)[:3]
    offset = Vec(*offset)[:3]

    bounds = Bbox(offset, shape + offset)

    alignment_check = bounds.round_to_chunk_size(meta.chunk_size(mip),
                                                 meta.voxel_offset(mip))

    if not np.all(alignment_check.minpt == bounds.minpt):
        raise AlignmentError(f"""
      Only chunk aligned writes are supported by this function. 

      Got:             {bounds}
      Volume Offset:   {meta.voxel_offset(mip)} 
      Nearest Aligned: {alignment_check}
    """)

    bounds = Bbox.clamp(bounds, meta.bounds(mip))

    img_offset = bounds.minpt - offset
    img_end = Vec.clamp(bounds.size3() + img_offset, Vec(0, 0, 0), shape)

    class ChunkIterator():
        def __len__(self):
            csize = meta.chunk_size(mip)
            bbox = Bbox(img_offset, img_end)
            # round up and avoid conversion to float
            n_chunks = (bbox.dx + csize[0] - 1) // csize[0]
            n_chunks *= (bbox.dy + csize[1] - 1) // csize[1]
            n_chunks *= (bbox.dz + csize[2] - 1) // csize[2]
            return n_chunks

        def __iter__(self):
            for startpt in xyzrange(img_offset, img_end, meta.chunk_size(mip)):
                startpt = startpt.clone()
                endpt = min2(startpt + meta.chunk_size(mip), shape)
                spt = (startpt + bounds.minpt).astype(int)
                ept = (endpt + bounds.minpt).astype(int)
                yield (startpt, endpt, spt, ept)

    return ChunkIterator()