def clusterstepframes(cr, info, leftstep, rightstep):
# Compute step times
stepactivity = cr.iloc[:, 16:24]
stepdiff = stepactivity.diff()
steppeaks = siphon.findpeaksMax(stepdiff, 1500)
pksloc = [[stepdiff.index.get_loc(peak) for peak in step]
for step in steppeaks]
# Tile step frames
vidpaths = activitymovies.getmoviepath(info)
timepaths = activitymovies.gettimepath(info)
backpaths = activitymovies.getbackgroundpath(info)
videos = [
video.video(path, timepath)
for path, timepath in zip(vidpaths, timepaths)
]
def getstepframes(stepindex, flip=False):
stepcenterxcm = stepcenters[stepindex][1] * preprocess.width_pixel_to_cm
framehead = [
p for p in pksloc[stepindex]
if (cr.xhead[p] < stepcenterxcm
if not flip else cr.xhead[p] > stepcenterxcm)
]
frames = [
imgproc.croprect(stepcenters[stepindex], (200, 200),
videos[0].frame(p)) for p in framehead
]
backgrounds = [
imgproc.croprect(
stepcenters[stepindex], (200, 200),
activitymovies.getbackground(backpaths[0],
videos[0].timestamps[p]))
for p in framehead
]
frames = [cv2.subtract(f, b) for f, b in zip(frames, backgrounds)]
if flip:
frames = [cv2.flip(f, 1) for f in frames]
return frames, framehead
leftframes, leftindices = getstepframes(leftstep, False)
rightframes, rightindices = getstepframes(rightstep, True)
frames = np.array(leftframes + rightframes)
frameindices = np.array(leftindices + rightindices)
sortindices = np.argsort(frameindices)
frames = frames[sortindices]
frameindices = frameindices[sortindices]
R, labels, h = imgproc.cluster(frames, videos[0], frameindices)
return frames, stepdiff, steppeaks, pksloc, R, labels
def clusterroiframes(act, roiactivity, info, leftroi, rightroi, roicenter_cm,
cropframes):
# Compute step times
roidiff = roiactivity.diff()
roipeaks = activitytables.findpeaks(roidiff, 1500)
pksloc = [[roidiff.index.get_loc(peak) for peak in roi]
for roi in roipeaks]
# Tile step frames
vidpaths = activitymovies.getmoviepath(info)
timepaths = activitymovies.gettimepath(info)
backpaths = activitymovies.getbackgroundpath(info)
videos = [
video.video(path, timepath)
for path, timepath in zip(vidpaths, timepaths)
]
def getroiframes(roiindex, flip=False):
roicenterxcm = roicenter_cm[roiindex][1]
headdistance = [act.xhead[p] - roicenterxcm for p in pksloc[roiindex]]
print headdistance
framehead = [
p for i, p in enumerate(pksloc[roiindex])
if (-25 < headdistance[i] < -5
if not flip else 5 < headdistance[i] < 25)
]
frames = [cropframes(videos[0].frame(p), roiindex) for p in framehead]
backgrounds = [
cropframes(
activitymovies.getbackground(backpaths[0],
videos[0].timestamps[p]),
roiindex) for p in framehead
]
frames = [cv2.subtract(f, b) for f, b in zip(frames, backgrounds)]
if flip:
frames = [cv2.flip(f, 1) for f in frames]
return frames, framehead
leftframes, leftindices = getroiframes(leftroi, False)
rightframes, rightindices = getroiframes(rightroi, True)
print "==========================="
frames = np.array(leftframes + rightframes)
frameindices = np.array(leftindices + rightindices)
sortindices = np.argsort(frameindices)
frames = frames[sortindices]
frameindices = frameindices[sortindices]
Z, R, labels, h = imgproc.cluster(frames, videos[0], frameindices)
return frames, roidiff, roipeaks, pksloc, Z, R, labels
def clusterroiframes(act, roiactivity, info, leftroi, rightroi, roicenter_cm, cropframes):
# Compute step times
roidiff = roiactivity.diff()
roipeaks = activitytables.findpeaks(roidiff, 1500)
pksloc = [[roidiff.index.get_loc(peak) for peak in roi] for roi in roipeaks]
# Tile step frames
vidpaths = activitymovies.getmoviepath(info)
timepaths = activitymovies.gettimepath(info)
backpaths = activitymovies.getbackgroundpath(info)
videos = [video.video(path, timepath) for path, timepath in zip(vidpaths, timepaths)]
def getroiframes(roiindex, flip=False):
roicenterxcm = roicenter_cm[roiindex][1]
headdistance = [act.xhead[p] - roicenterxcm for p in pksloc[roiindex]]
print headdistance
framehead = [
p
for i, p in enumerate(pksloc[roiindex])
if (-25 < headdistance[i] < -5 if not flip else 5 < headdistance[i] < 25)
]
frames = [cropframes(videos[0].frame(p), roiindex) for p in framehead]
backgrounds = [
cropframes(activitymovies.getbackground(backpaths[0], videos[0].timestamps[p]), roiindex) for p in framehead
]
frames = [cv2.subtract(f, b) for f, b in zip(frames, backgrounds)]
if flip:
frames = [cv2.flip(f, 1) for f in frames]
return frames, framehead
leftframes, leftindices = getroiframes(leftroi, False)
rightframes, rightindices = getroiframes(rightroi, True)
print "==========================="
frames = np.array(leftframes + rightframes)
frameindices = np.array(leftindices + rightindices)
sortindices = np.argsort(frameindices)
frames = frames[sortindices]
frameindices = frameindices[sortindices]
Z, R, labels, h = imgproc.cluster(frames, videos[0], frameindices)
return frames, roidiff, roipeaks, pksloc, Z, R, labels
def clusterstepframes(cr,info,leftstep,rightstep):
# Compute step times
stepactivity = cr.iloc[:,16:24]
stepdiff = stepactivity.diff()
steppeaks = siphon.findpeaksMax(stepdiff,1500)
pksloc = [[stepdiff.index.get_loc(peak) for peak in step] for step in steppeaks]
# Tile step frames
vidpaths = activitymovies.getmoviepath(info)
timepaths = activitymovies.gettimepath(info)
backpaths = activitymovies.getbackgroundpath(info)
videos = [video.video(path,timepath) for path,timepath in zip(vidpaths,timepaths)]
def getstepframes(stepindex,flip=False):
stepcenterxcm = stepcenters[stepindex][1] * preprocess.width_pixel_to_cm
framehead = [p for p in pksloc[stepindex]
if (cr.xhead[p] < stepcenterxcm if not flip else cr.xhead[p] > stepcenterxcm)]
frames = [imgproc.croprect(stepcenters[stepindex],(200,200),videos[0].frame(p))
for p in framehead]
backgrounds = [imgproc.croprect(stepcenters[stepindex],(200,200),activitymovies.getbackground(backpaths[0],videos[0].timestamps[p]))
for p in framehead]
frames = [cv2.subtract(f,b) for f,b in zip(frames,backgrounds)]
if flip:
frames = [cv2.flip(f,1) for f in frames]
return frames,framehead
leftframes,leftindices = getstepframes(leftstep,False)
rightframes,rightindices = getstepframes(rightstep,True)
frames = np.array(leftframes + rightframes)
frameindices = np.array(leftindices + rightindices)
sortindices = np.argsort(frameindices)
frames = frames[sortindices]
frameindices = frameindices[sortindices]
R,labels,h = imgproc.cluster(frames,videos[0],frameindices)
return frames,stepdiff,steppeaks,pksloc,R,labels
