geowatch.tasks.depth.utils module

geowatch.tasks.depth.utils.process_image_chunked(image, process_func, chip_size=(2048, 2048, 3), overlap=(128, 128, 0), output_dtype=<class 'numpy.uint8'>, verbose=1, sliding_window_method='kwarray')

Parameters:

chip_size – must be less than half of the overlap

Example

>>> from geowatch.tasks.depth.utils import *  # NOQA
>>> import kwimage
>>> import kwarray
>>> image = kwimage.ensure_float01(kwimage.grab_test_image(dsize=(512, 512)))
>>> nan_poly = kwimage.Polygon.random(rng=None).scale(image.shape[0])
>>> image = nan_poly.fill(image.copy(), np.nan)
>>> process_func = lambda x: kwimage.gaussian_blur(x, sigma=7).mean(axis=2)
>>> non_chunked = process_func(image)
>>> chip_size = (128, 128, 3)
>>> overlap = (32, 32, 0)
>>> output_dtype = np.uint8
>>> verbose = 0
>>> print('kwarray')
>>> result1 = process_image_chunked(image, process_func, chip_size, overlap, output_dtype, verbose=1, sliding_window_method='kwarray')
>>> print('dask')
>>> result2 = process_image_chunked(image, process_func, chip_size, overlap, output_dtype, verbose=1, sliding_window_method='dask')
>>> # xdoctest: +REQUIRES(--show)
>>> import kwplot
>>> kwplot.autompl()
>>> kwplot.imshow(image, pnum=(1, 3, 1), doclf=True)
>>> kwplot.imshow(result1, pnum=(1, 3, 2), title='kwarray')
>>> kwplot.imshow(result2, pnum=(1, 3, 3), title='dask')