Reduce memory usage

[geospatial-jeff]

Aiocogeo uses ~4x more memory than rio tiler when reading a single tile:

Line #    Mem usage    Increment   Line Contents
================================================
    44    115.3 MiB    115.3 MiB   @profile
    45                             def main():
    46    125.7 MiB     10.4 MiB       asyncio.run(_aiocogeo())
    47    128.5 MiB      2.8 MiB       rio_tile()

The culprit is the call to skimage.resize when resampling the image:

Line #    Mem usage    Increment   Line Contents
================================================
   292    118.9 MiB    118.9 MiB       @profile
   293                                 def _postprocess(
   294                                     self, arr: NpArrayType, img_tiles: TileMetadata, out_shape: Tuple[int, int]
   295                                 ) -> NpArrayType:
   296                                     """Wrapper around ``_clip_array`` and ``_resample`` to postprocess the partial read"""
   297    118.9 MiB      0.0 MiB           return self._resample(
   298    126.5 MiB      7.6 MiB               self._clip_array(arr, img_tiles), img_tiles=img_tiles, out_shape=out_shape
   299                                     )

[geospatial-jeff]

Its much better with PIL.Image.resize

Line #    Mem usage    Increment   Line Contents
================================================
   298    118.4 MiB    118.4 MiB       @profile
   299                                 def _postprocess(
   300                                     self, arr: NpArrayType, img_tiles: TileMetadata, out_shape: Tuple[int, int]
   301                                 ) -> NpArrayType:
   302                                     """Wrapper around ``_clip_array`` and ``_resample`` to postprocess the partial read"""
   303    118.4 MiB      0.0 MiB           return self._resample(
   304    118.9 MiB      0.5 MiB               self._clip_array(arr, img_tiles), img_tiles=img_tiles, out_shape=out_shape
   305                                     )