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import numpy as np
def pretty_depth(depth):
"""Converts depth into a 'nicer' format for display
This is abstracted to allow for experimentation with normalization
Args:
depth: A numpy array with 2 bytes per pixel
Returns:
A numpy array that has been processed whos datatype is unspecified
"""
np.clip(depth, 0, 2**10 - 1, depth)
depth >>= 2
depth = depth.astype(np.uint8)
return depth
def pretty_depth_cv(depth):
"""Converts depth into a 'nicer' format for display
This is abstracted to allow for experimentation with normalization
Args:
depth: A numpy array with 2 bytes per pixel
Returns:
An opencv image who's datatype is unspecified
"""
import cv
depth = pretty_depth(depth)
image = cv.CreateImageHeader((depth.shape[1], depth.shape[0]),
cv.IPL_DEPTH_8U,
1)
cv.SetData(image, depth.tostring(),
depth.dtype.itemsize * depth.shape[1])
return image
def video_cv(video):
"""Converts video into a BGR format for opencv
This is abstracted out to allow for experimentation
Args:
video: A numpy array with 1 byte per pixel, 3 channels RGB
Returns:
An opencv image who's datatype is 1 byte, 3 channel BGR
"""
import cv
video = video[:, :, ::-1] # RGB -> BGR
image = cv.CreateImageHeader((video.shape[1], video.shape[0]),
cv.IPL_DEPTH_8U,
3)
cv.SetData(image, video.tostring(),
video.dtype.itemsize * 3 * video.shape[1])
return image
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