def run_depth_utils_example():
"""
FUNC: examples of basic usage of depth utils
"""
# # load binary depth file
# depthFile = './depth_data/a01_s01_e01_sdepth.bin'
# depthSequence = loadDepthFile(depthFile, fType = 'bin')
# load png depth files in a given path
depthFilePath = './depth_data/d_a01_s01_e01_sdepth/'
depthSequence = loadDepthFile(depthFilePath, fType='png')
for depthData in depthSequence:
# show depth data
showDepthData(depthData)
# show 3d points
points = getWorldCoordinates(depthData)
visualizePointCloud(points)
projData = getFrontDepthProjections(points, projSize=depthData.shape)
# projImg = getDepthProjections(points)
showDepthData(projData)
r_alpha = math.pi / 2. # angle around x-axis
r_beta = 0 # angle around y-axis
r_points = rotatePoints(points, r_alpha, r_beta)
visualizePointCloud(r_points)
projData = getDepthProjection(r_points)
showDepthData(projData)
def run_depth_utils_example():
"""
FUNC: examples of basic usage of depth utils
"""
# # load binary depth file
# depthFile = './depth_data/a01_s01_e01_sdepth.bin'
# depthSequence = loadDepthFile(depthFile, fType = 'bin')
# load png depth files in a given path
depthFilePath = './depth_data/d_a01_s01_e01_sdepth/'
depthSequence = loadDepthFile(depthFilePath, fType = 'png')
for depthData in depthSequence:
# show depth data
showDepthData(depthData)
# show 3d points
points = getWorldCoordinates(depthData)
visualizePointCloud(points)
projData = getFrontDepthProjections(points, projSize = depthData.shape)
# projImg = getDepthProjections(points)
showDepthData(projData)
r_alpha = math.pi / 2. # angle around x-axis
r_beta = 0 # angle around y-axis
r_points = rotatePoints(points, r_alpha, r_beta)
visualizePointCloud(r_points)
projData = getDepthProjection(r_points)
showDepthData(projData)
def rotateDepthSequence(frames, r_alpha, r_beta):
"""
FUNC: rotate depth frames in a sequence
PARAM:
frames: a list of frames
r_alpha: angle around y-axis
r_beta: angle around x-axis
RETURN:
r_frames: a list of rotated frames
"""
r_frames = []
for depthData in frames:
points = getWorldCoordinates(depthData)
r_points = rotatePoints(points, r_alpha, r_beta)
projData = getDepthProjection(r_points, isCrop=False)
r_frames.append(projData)
return r_frames
def rotateDepthSequence(frames, r_alpha, r_beta):
"""
FUNC: rotate depth frames in a sequence
PARAM:
frames: a list of frames
r_alpha: angle around y-axis
r_beta: angle around x-axis
RETURN:
r_frames: a list of rotated frames
"""
r_frames = []
for depthData in frames:
points = getWorldCoordinates(depthData)
r_points = rotatePoints(points, r_alpha, r_beta)
projData = getDepthProjection(r_points, isCrop=False)
r_frames.append(projData)
return r_frames
# def calWinDepthMHIList(frames, winSize, winStep):
# """ calculate dmhi list using sliding window """
# dmhiList = []
# for i in xrange(0, len(frames), winStep):
# startIdx = i
# endIdx = i + winSize - 1
# if endIdx <= len(frames) - 1:
# # print "startIdx: %d, endIdx: %d" % (startIdx, endIdx)
# winFrames = frames[startIdx:endIdx]
# dmhiImg = calDepthMHI(winFrames)
# dmhiList.append(dmhiImg)
#
# return dmhiList
#
#
# def calPyramidDepthMHIList(frames, dHOGTemporalPyramids):
# """ calculate temporal Pyramid Depth MHI (PDMHI) list"""
# pdmhiList = []
# for l in dHOGTemporalPyramids:
# wantedParts = l
# segmentedList = split_list(frames, wantedParts)
#
# for segment in segmentedList:
# tmpFrames = segment
# dmhiImg = calDepthMHI(tmpFrames)
#
# pdmhiList.append(dmhiImg)
#
# return pdmhiList
#
#
# def cropAndResizeImageList1(imageList, newSize = (128, 128)):
# """ crop the image list and resize them (overall)"""
# firstImg = imageList[0]
# finalTop, finalBottom, finalLeft, finalRight = findBoxRegion(firstImg)
#
# for i in xrange(1, len(imageList)):
# currImg = imageList[i]
# currTop, currBottom, currLeft, currRight = findBoxRegion(currImg)
#
# if currTop < finalTop:
# finalTop = currTop
#
# if currBottom > finalBottom:
# finalBottom = currBottom
#
# if currLeft < finalLeft:
# finalLeft = currLeft
#
# if currRight > finalRight:
# finalRight = currRight
#
# postprocessImageList = []
# for image in imageList:
# cropedImage = image[finalTop:finalBottom, finalLeft:finalRight]
# resizedImage = cv2.resize(cropedImage, newSize)
# postprocessImageList.append(resizedImage)
#
# # # show image
# # cv2.imshow('', resizedImage)
# # cv2.waitKey()
#
# return postprocessImageList
#
#
# def findBoxRegion(image):
# """ find the box region of given image """
# # top
# rows, cols = image.shape
# top = 0
# for r in xrange(rows):
# row = image[r, :]
# if sum(row) > 0:
# top = r
# break
#
# # bottom
# bottom = rows - 1
# for r in xrange(rows-1, -1, -1):
# row = image[r, :]
# if sum(row) > 0:
# bottom = r
# break;
#
# # left
# left = 0
# for c in xrange(cols):
# col = image[:, c]
# if sum(col) > 0:
# left = c
# break
#
# # right
# right = cols - 1
# for c in xrange(cols-1, -1, -1):
# col = image[:, c]
# if sum(col) > 0:
# right = c
# break
#
# return top, bottom, left, right
#
#
# def cropAndResizeImageList2(imageList, newSize = (128, 128)):
# """ crop ROI from an image (one by one) """
# postprocessImageList = []
# for image in imageList:
# top, bottom, left, right = findBoxRegion(image)
# cropedImage = image[top:bottom, left:right]
# resizedImage = cv2.resize(cropedImage, newSize)
# postprocessImageList.append(resizedImage)
#
# return postprocessImageList
#
#
# def cropAndResizeImageList3(imageList, maxImSize = 300):
# """ crop ROI from an image (one by one) """
# postprocessImageList = []
# for image in imageList:
# top, bottom, left, right = findBoxRegion(image)
# cropedImage = image[top:bottom, left:right]
# resizedImage = resizeImage(cropedImage, maxImSize)
# postprocessImageList.append(resizedImage)
#
# return postprocessImageList
#
#
# def resizeImage(originalImg, maxImSize):
# """
# maxImSize -maximum size of the input image
# """
# nCols, nRows = originalImg.shape
#
# if max(nCols, nRows) > maxImSize:
# fx = float(maxImSize)/max(nCols, nRows)
# resizedImg = cv2.resize(originalImg, (0,0), fx=fx, fy=fx, interpolation = cv2.INTER_CUBIC)
# else:
# resizedImg = originalImg.copy()
#
# return resizedImg
#
#
# def computeHMHT(imageList):
# """ compute hierarchical motion history templates """
# strides = config.strides
# hmhtList = []
# for stride in strides:
# dmhiImg = calDepthMHI(imageList, motion_thresh = 10, stride = stride)
#
# # find ROI
# top, bottom, left, right = findBoxRegion(dmhiImg)
# cropedImage = dmhiImg[top:bottom, left:right]
# resizedImage = cv2.resize(cropedImage, (128, 128))
# hmhtList.append(resizedImage)
#
# return hmhtList