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import typing # NOQA
import matplotlib
import numpy as np
from .normalize import normalize
class Depth2RGB(object):
"""Convert depth array to rgb.
Parameters
----------
min_value: float, optional
Minimum value for colorizing.
max_value: float, optional
Maximum value for colorizing.
colormap: str, optional
Colormap, default: 'jet'.
"""
def __init__(self, min_value=None, max_value=None, colormap="jet"):
self._min_value = min_value
self._max_value = max_value
self._colormap = colormap
@property
def min_value(self):
"""Minimum value of depth."""
return self._min_value
@property
def max_value(self):
"""Maximum value of depth."""
return self._max_value
def __call__(self, depth, dtype=np.uint8):
"""Convert depth array to rgb.
Parameters
----------
depth: numpy.ndarray, (H, W), float
Depth image.
dtype: numpy.dtype
Dtype of output image. default: np.uint8
Returns
-------
rgb: numpy.ndarray, (H, W, 3), np.uint8
Output colorized image.
"""
assert depth.ndim == 2, "depth image must be 2 dimensional"
assert np.issubdtype(depth.dtype, np.floating), "depth dtype must be float"
normalized, self._min_value, self._max_value = normalize(
depth,
min_value=self._min_value,
max_value=self._max_value,
return_minmax=True,
)
isnan = np.isnan(normalized)
normalized[isnan] = 0
if isinstance(self._colormap, str):
if hasattr(matplotlib, "colormaps"):
colormap_func = matplotlib.colormaps[self._colormap]
else:
colormap_func = matplotlib.cm.get_cmap(self._colormap)
else:
colormap_func = self._colormap
rgb = colormap_func(normalized)[:, :, :3]
rgb[isnan] = (0, 0, 0)
if dtype == np.uint8:
rgb = (rgb * 255).round().astype(np.uint8)
else:
assert np.issubdtype(dtype, np.floating)
rgb = rgb.astype(dtype)
return rgb
def depth2rgb(
depth,
min_value=None,
max_value=None,
colormap="jet",
dtype=np.uint8,
):
# type: (np.ndarray, typing.Optional[float], typing.Optional[float], str, typing.Type) -> np.ndarray # NOQA
"""Convert depth to rgb.
Parameters
----------
depth: numpy.ndarray, (H, W), float
Depth image.
dtype: numpy.dtype
Dtype of output image. default: np.uint8
min_value: float, optional
Minimum value for colorizing.
max_value: float, optional
Maximum value for colorizing.
colormap: str, optional
Colormap, default: 'jet'.
Returns
-------
rgb: numpy.ndarray, (H, W, 3), np.uint8
Output colorized image.
"""
return Depth2RGB(min_value, max_value, colormap)(depth, dtype)
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