def cook(self, location, interface, attrs):
if not 'xcp' in attrs or not attrs['xcp']: return
if self.mats is None:
xcp_filename = self.resolvePath(attrs['xcp'])
try:
self.mats, self.xcp_data = ViconReader.loadXCP(xcp_filename)
self.Ps = interface.getPsFromMats(self.mats)
except IOError as e:
self.logger.error('Could not load XCP file: %s' % str(e))
return False
interface.setAttr('mats', self.mats)
interface.setAttr('xcp_data', self.xcp_data)
xcp_camera_ids = np.array([int(x['DEVICEID']) for x in self.xcp_data],
dtype=np.int32)
camera_names = [
'%s:%s' % (x['LABEL'], x['DEVICEID']) for x in self.xcp_data
]
self.setupAttrs = {
'Ps': self.Ps,
'camera_ids': xcp_camera_ids,
'camera_names': camera_names,
'mats': self.mats
}
interface.createChild('cameras',
'cameras',
atLocation=location,
attrs=self.setupAttrs)
def setup(self, interface, attrs):
if not 'x2d' in attrs or not attrs['x2d']: return
x2d_filename = self.resolvePath(attrs['x2d'])
if self.isDirty('x2d'):
try:
x2d_dict = ViconReader.loadX2D(x2d_filename)
self.x2d_frames = x2d_dict['frames']
self.header = x2d_dict['header']
except IOError as e:
self.logger.error('Could not load X2D file: %s' % str(e))
return False
self.firstFrame, self.lastFrame = max(
0, interface.frame()), len(x2d_dict)
def setup(self, interface, attrs):
if not 'xcp' in attrs or not attrs['xcp']: return
if not 'x2d' in attrs or not attrs['x2d']: return
# if self.isDirty('xcp') or self.isDirty('x2d'):
if self.x2d_frames is None:
xcp_filename = self.resolvePath(attrs['xcp'])
x2d_filename = self.resolvePath(attrs['x2d'])
# Note: Remove x2d_frames condition when dirty states are more reliable
try:
Ps, self.mats, camera_ids, camera_names, self.x2d_frames, header = ViconReader.load_xcp_and_x2d(
xcp_filename, x2d_filename)
except IOError as e:
self.logger.error('Could not load XCP and X2D files: %s' %
str(e))
return False
offset = attrs['offset']
# Find timecode in header
for info in header:
if info[0] == 1:
# The timecode should be last
tcStr = info[-1]
tcElms = tcStr.split()[:4]
self.timecode = ':'.join(tcElms)
self.logger.info('Timecode found: %s' % self.timecode)
break
tcSyncTime, self.offset = interface.getTimecodeSync(
self.timecode, 'timecodeLocation', attrs, 100, 25., 4.,
attrs['offset'])
if tcSyncTime:
self.logger.info('Setting timecode to: %s (offset = %d)' %
(tcSyncTime, self.offset))
self.firstFrame, self.lastFrame = max(0, interface.frame()), len(
self.x2d_frames)
if attrs['reverse']: self.x2d_frames = self.x2d_frames[::-1]
self.setupAttrs = {
'Ps': Ps,
'camera_ids': camera_ids,
'camera_names': camera_names,
'mats': self.mats
}
GL.glDisableClientState(GL.GL_VERTEX_ARRAY)
# GL.glEnable(GL.GL_CULL_FACE)
# GL.glCullFace(GL.GL_BACK)
# GL.glFrontFace(GL.GL_CCW)
# GL.glVertexPointerf(self.cameraPointArray)
# GL.glColorPointerf(self.cameraColourArray)
# GL.glDrawElementsui(GL.GL_TRIANGLES, self.cameraIdxArray)
# GL.glDisableClientState(GL.GL_COLOR_ARRAY)
if __name__ == '__main__':
import sys, os
directory = os.environ['GRIP_DATA']
xcp_filename = os.path.join(directory, sys.argv[1])
from IO import ViconReader
mats, xcp_data = ViconReader.loadXCP(xcp_filename)
from UI import QAppCtx
from UI.QGLViewer import Camera
from UI.QApp import QApp
with QAppCtx():
glWidget = QApp()
n = len(mats)
camera_ids = range(len(mats[:n]))
cameras = []
for mat, cid in zip(mats, camera_ids)[:n]:
camera = Camera('Cam_%d' % cid)
glWidget.view().addCamera(camera)
cameras.append(camera)
camera.setP(mat[2], distortion=mat[3])
def main():
global State, mats, movieFilenames, primitives
global movies, primitives2D, deinterlacing, detectingWands
import IO
import sys, os
deinterlacing = False
detectingWands = False
detectingTiara = False
dot_detections = None
detections_filename = None
frame_offsets = None
firstFrame, lastFrame = 0, 5000
drawDotSize = 4.0
fovX, (ox,
oy), pan_tilt_roll, tx_ty_tz, distortion = 50., (0,
0), (0, 0,
0), (0, 1250,
0), (0,
0)
mats = []
grip_directory = os.environ['GRIP_DATA']
if 0:
fovX, (ox, oy), pan_tilt_roll, tx_ty_tz, distortion = 37.9, (0, 0), (
-66.0, 3.5, -0.2), (4850, 1330, 3280), (0, 0) # roughed in
K, RT = Calibrate.composeK(fovX, ox, oy), Calibrate.composeRT(
Calibrate.composeR(pan_tilt_roll), tx_ty_tz, 0)
mat0 = [
K[:3, :3], RT[:3, :4],
np.dot(K, RT)[:3, :], distortion, -np.dot(RT[:3, :3].T, RT[:3, 3]),
[1920, 1080]
]
fovX, (ox, oy), pan_tilt_roll, tx_ty_tz, distortion = 55.8, (0, 0), (
-103.6, 3.5, -0.3), (2980, 1380, -2180), (0, 0) # roughed in
K, RT = Calibrate.composeK(fovX, ox, oy), Calibrate.composeRT(
Calibrate.composeR(pan_tilt_roll), tx_ty_tz, 0)
mat1 = [
K[:3, :3], RT[:3, :4],
np.dot(K, RT)[:3, :], distortion, -np.dot(RT[:3, :3].T, RT[:3, 3]),
[1920, 1080]
]
fovX, (ox, oy), pan_tilt_roll, tx_ty_tz, distortion = 49.3, (0, 0), (
27.9, 4.0, -0.2), (-5340, 1150, 5030), (0, 0) # roughed in
K, RT = Calibrate.composeK(fovX, ox, oy), Calibrate.composeRT(
Calibrate.composeR(pan_tilt_roll), tx_ty_tz, 0)
mat2 = [
K[:3, :3], RT[:3, :4],
np.dot(K, RT)[:3, :], distortion, -np.dot(RT[:3, :3].T, RT[:3, 3]),
[1920, 1080]
]
fovX, (ox, oy), pan_tilt_roll, tx_ty_tz, distortion = 50.6, (0, 0), (
-156.6, 4.9, 0.2), (-105, 1400, -4430), (0, 0) # roughed in
K, RT = Calibrate.composeK(fovX, ox, oy), Calibrate.composeRT(
Calibrate.composeR(pan_tilt_roll), tx_ty_tz, 0)
mat3 = [
K[:3, :3], RT[:3, :4],
np.dot(K, RT)[:3, :], distortion, -np.dot(RT[:3, :3].T, RT[:3, 3]),
[1920, 1080]
]
mats = [mat0, mat1, mat2, mat3]
xcp_filename = '154535_Cal168_Floor_Final.xcp'
directory = os.path.join(grip_directory, 'REFRAME')
movieFilenames = [
'001E0827_01.MP4', '001F0813_01.MP4', '001G0922_01.MP4',
'001H0191_01.MP4'
]
#mats,movieFilenames = mats[:1],movieFilenames[:1] # restrict to single-view
frame_offsets = [119 + 160, 260, 339, 161]
small_blur, large_blur = 1, 25
min_dot_size = 1.0
max_dot_size = 20.0
circularity_threshold = 3.0
threshold_bright, threshold_dark_inv = 250, 250 #135,135
elif 0:
xcp_filename = '201401211653-4Pico-32_Quad_Dialogue_01_Col_wip_01.xcp'
detections_filename = 'detections.dat'
detectingTiara = True
pan_tilt_roll = (0, 0, 90)
distortion = (0.291979, 0.228389)
directory = os.path.join(os.environ['GRIP_DATA'], 'ted')
movieFilenames = [
'201401211653-4Pico-32_Quad_Dialogue_01_%d.mpg' % xi
for xi in range(1)
]
firstFrame = 511
small_blur, large_blur = 1, 20
min_dot_size = 1.0
max_dot_size = 16.0
circularity_threshold = 3.0
threshold_bright, threshold_dark_inv = 0, 170
elif 1:
xcp_filename = '50_Grip_RoomCont_AA_02.xcp'
detections_filename = 'detections.dat'
pan_tilt_roll = (0, 0, 0)
distortion = (0.291979, 0.228389)
directory = os.path.join(os.environ['GRIP_DATA'], '151110')
movieFilenames = ['50_Grip_RoomCont_AA_02.v2.mov']
firstFrame = 0
small_blur, large_blur = 1, 20
min_dot_size = 1.0
max_dot_size = 16.0
circularity_threshold = 3.0
threshold_bright, threshold_dark_inv = 170, 170
attrs = dict([(v, eval(v)) for v in [
'small_blur', 'large_blur', 'threshold_bright', 'threshold_dark_inv',
'circularity_threshold', 'min_dot_size', 'max_dot_size'
]])
primitives2D = QGLViewer.makePrimitives2D(([], []), ([], []))
primitives = []
if len(movieFilenames) is 1:
# TODO: time_base, timecode
K, RT = Calibrate.composeK(fovX, ox, oy), Calibrate.composeRT(
Calibrate.composeR(pan_tilt_roll), tx_ty_tz, 0)
mats = [[
K[:3, :3], RT[:3, :4],
np.dot(K, RT)[:3, :], distortion, -np.dot(RT[:3, :3].T, RT[:3, 3]),
[1920, 1080]
]]
camera_ids = ['video']
movies = [
MovieReader.open_file(os.path.join(directory, movieFilenames[0]),
audio=False)
]
else: # hard coded cameras
if xcp_filename.endswith('.xcp'):
if detectingTiara: # gruffalo
c3d_filename = os.path.join(
directory,
'201401211653-4Pico-32_Quad_Dialogue_01_Col_wip_02.c3d')
from IO import C3D
c3d_dict = C3D.read(c3d_filename)
global c3d_frames
c3d_frames, c3d_fps, c3d_labels = c3d_dict['frames'], c3d_dict[
'fps'], c3d_dict['labels']
c3d_subject = '' #'TedFace'
which = np.where(
[s.startswith(c3d_subject) for s in c3d_labels])[0]
c3d_frames = c3d_frames[:, which, :]
c3d_labels = [c3d_labels[i] for i in which]
print len(c3d_frames)
xcp, xcp_data = ViconReader.loadXCP(
os.path.join(directory, xcp_filename))
mats.extend(xcp)
elif xcp_filename.endswith('.cal'):
from IO import OptitrackReader
xcp, xcp_data = OptitrackReader.load_CAL(
os.path.join(directory, xcp_filename))
mats = xcp
print 'mats', len(mats), len(movieFilenames)
assert (len(mats) == len(movieFilenames))
camera_ids = []
movies = []
for ci, mf in enumerate(movieFilenames):
fo = 0 if frame_offsets is None else frame_offsets[ci]
movies.append(
MovieReader.open_file(os.path.join(directory, mf),
audio=False,
frame_offset=fo))
camera_ids = ['cam_%d' % ci for ci in xrange(len(mats))]
print len(mats), len(movies), len(camera_ids)
primitives.append(GLPoints3D([]))
primitives.append(GLPoints3D([]))
primitives.append(GLPoints3D([]))
primitives[0].colour = (0, 1, 1, 0.5) # back-projected "cyan" points
primitives[1].colour = (0, 0, 1, 0.5)
primitives[1].pointSize = 5
primitives[2].colour = (1, 0, 0, 0.99)
if len(movieFilenames) != 1 and detections_filename != None:
try:
dot_detections = IO.load(detections_filename)[1]
except:
numFrames = len(c3d_frames) # TODO HACK HACK
dot_detections = movies_to_detections(movies, range(numFrames),
deinterlacing, attrs)
IO.save(detections_filename, dot_detections)
if detectingTiara:
x3ds_seq = {}
for fi in dot_detections.keys():
frame = c3d_frames[(fi - 55) % len(c3d_frames)]
which = np.array(np.where(frame[:, 3] == 0)[0], dtype=np.int32)
x3ds_seq[fi] = np.concatenate((VICON_tiara_x3ds + np.array([150,-100,0],dtype=np.float32),frame[which,:3])), \
np.concatenate((np.arange(len(VICON_tiara_x3ds),dtype=np.int32),which+len(VICON_tiara_x3ds)))
dot_labels = get_labels(dot_detections.keys(),
x3ds_seq,
dot_detections,
mats,
x2d_threshold=0.05)
calibration_fi = 546 - 2 - 6
RT = tighten_calibration(x3ds_seq[calibration_fi],
dot_labels[calibration_fi], mats)
for v in c3d_frames:
v[:, :3] = np.dot(v[:, :3], RT[:3, :3].T) + RT[:, 3]
if True:
dot_detections = IO.load(detections_filename)[1]
x3ds_seq = {}
for fi in dot_detections.keys():
frame = c3d_frames[(fi - 55) % len(c3d_frames)]
which = np.array(np.where(frame[:, 3] == 0)[0],
dtype=np.int32)
x3ds_seq[fi] = np.concatenate((VICON_tiara_x3ds + np.array([0,1000,0],dtype=np.float32),frame[which,:3])), \
np.concatenate((np.arange(len(VICON_tiara_x3ds),dtype=np.int32),which+len(VICON_tiara_x3ds)))
#dot_labels = get_labels(dot_detections.keys(), x3ds_seq, dot_detections, mats, x2d_threshold = 0.05)
if detectingTiara:
primitives.append(GLPoints3D(VICON_tiara_x3ds + [0, 1000, 0]))
primitives[-1].pointSize = 5
global track3d, prev_frame, booting, trackGraph
track3d = Label.Track3D(mats[:len(movies)],
x2d_threshold=0.03,
x3d_threshold=5.0,
min_rays=3,
boot_interval=2) #tilt_threshold = 0.01, gruffalo
trackGraph = Label.TrackGraph()
prev_frame = 0
booting = 1
from UI import QApp
from PySide import QtGui
from GCore import State
# Modified the options parameter for fields to be the range of acceptable values for the box
# Previously would crash if small_blur got too low
QApp.fields = {
'image filter': [
('small_blur', 'Small blur radius',
'This is part of the image filter which controls the size of smallest detected features.',
'int', small_blur, {
"min": 0,
"max": None
}),
('large_blur', 'Large blur radius',
'This is part of the image filter which controls the size of largest detected features.',
'int', large_blur, {
"min": 0,
"max": None
}),
('threshold_bright', 'threshold_bright',
'This is part of the image filter which controls the size of smallest detected features.',
'int', threshold_bright, {
"min": 0,
"max": 255
}),
('threshold_dark_inv', 'threshold_dark_inv',
'This is part of the image filter which controls the size of largest detected features.',
'int', threshold_dark_inv, {
"min": 0,
"max": 255
}),
('circularity_threshold', 'circularity_threshold',
'How circular?.', 'float', circularity_threshold, {
"min": 0,
"max": 100
}),
('min_dot_size', 'min_dot_size',
'min_dot_size smallest detected features.', 'float', min_dot_size,
{
"min": 0,
"max": 100
}),
('max_dot_size', 'max_dot_size',
'max_dot_size largest detected features.', 'float', max_dot_size,
{
"min": 0,
"max": 100
}),
]
}
State.addKey('dotParams', {'type': 'image filter', 'attrs': attrs})
State.setSel('dotParams')
appIn = QtGui.QApplication(sys.argv)
appIn.setStyle('plastique')
win = QApp.QApp()
win.setWindowTitle('Imaginarium Dots Viewer')
QGLViewer.makeViewer(primitives=primitives,
primitives2D=primitives2D,
timeRange=(firstFrame, lastFrame),
callback=setFrame,
mats=mats,
camera_ids=camera_ids,
movies=movies,
pickCallback=picked,
appIn=appIn,
win=win)
def setFrame(frame):
global State, mats, movieFilenames, primitives
global movies, primitives2D, deinterlacing, detectingWands, dot_detections, track3d, prev_frame, booting, trackGraph
key = State.getKey('dotParams/attrs')
skipping, prev_frame = (frame != prev_frame
and frame - 1 != prev_frame), frame
booting = 10 if skipping else booting - 1
p0, p1 = [], []
if True: #dot_detections is None:
for pair in enumerate(movies):
pts = process_frame(deinterlacing, detectingWands, frame, key,
pair)
p0.append(pts[0])
p1.append(pts[1])
def make_bounds(lens):
return np.array([sum(lens[:x]) for x in xrange(len(lens) + 1)],
dtype=np.int32)
data0 = np.array(np.concatenate(p0),
dtype=np.float32).reshape(-1, 2), make_bounds(
map(len, p0))
data1 = np.array(np.concatenate(p1),
dtype=np.float32).reshape(-1, 2), make_bounds(
map(len, p1))
else:
#dot_detections = movies_to_detections(movies, [frame], deinterlacing, key)
data0, data1 = dot_detections[frame] if dot_detections.has_key(
frame) else dot_detections.values()[0]
for ci, md in enumerate(movies):
try:
MovieReader.readFrame(md, seekFrame=frame)
except:
print 'oops', frame
return None, None
#img = np.frombuffer(md['vbuffer'],dtype=np.uint8).reshape(md['vheight'],md['vwidth'],3)
QApp.view().cameras[ci + 1].invalidateImageData()
data0 = data0[0].copy(), data0[
1] # so that undistort doesn't modify the raw detections
data1 = data1[0].copy(), data1[1]
# TODO, move this to the viewer...
data0 = ViconReader.frameCentroidsToDets(data0, mats)
data1 = ViconReader.frameCentroidsToDets(data1, mats)
primitives2D[0].setData(data0[0], data0[1])
primitives2D[1].setData(data1[0], data1[1])
#print x2ds_labels
if len(movieFilenames) is not 1:
if 1:
#x2ds_data, x2ds_splits = data0 # dark points only
x2ds_data, x2ds_splits = data1 # light points only
if skipping:
x3ds, x3ds_labels = track3d.boot(x2ds_data, x2ds_splits)
#trackGraph = Label.TrackGraph()
else:
x3ds, x3ds_labels = track3d.push(x2ds_data, x2ds_splits)
# coarse bounding box
if False:
for xi, x in zip(x3ds_labels, x3ds):
if x[0] < -200 or x[0] > 200 or x[1] < 800 or x[
1] > 1200 or x[2] < -50 or x[2] > 300:
track3d.x2ds_labels[np.where(
track3d.x2ds_labels == xi)[0]] = -1
x[:] = 0
primitives[0].setData(x3ds)
#trackGraph.push(x3ds,x3ds_labels)
#primitives[0].graph = trackGraph.drawing_graph()
elif False:
Ps = np.array([m[2] / (m[0][0, 0]) for m in mats],
dtype=np.float32)
data = data0 # dark points
#data = data1 # light points
x3ds, x2ds_labels = Recon.intersect_rays(data[0],
data[1],
Ps,
mats,
tilt_threshold=0.003,
x2d_threshold=0.02,
x3d_threshold=5.0,
min_rays=2)
primitives[0].setData(x3ds)
if detectingTiara:
global c3d_frames
frame = c3d_frames[(frame - 55) % len(c3d_frames)]
which = np.where(frame[:, 3] == 0)[0]
x3ds = frame[which, :3]
#print frame,'len',len(x3ds)
primitives[1].setData(x3ds)
QApp.app.refreshImageData()
QApp.app.updateGL()
def main(x2d_filename, xcp_filename, c3d_filename=None):
'''Generate a 3D view of an x2d file, using the calibration.'''
global x2d_frames, mats, Ps, c3d_frames, primitives, primitives2D, track3d, prev_frame, track_orn, orn_graph, boot, orn_mapper, mar_mapper
prev_frame = None
c3d_frames = None
if c3d_filename != None:
c3d_dict = C3D.read(c3d_filename)
c3d_frames, c3d_fps, c3d_labels = c3d_dict['frames'], c3d_dict[
'fps'], c3d_dict['labels']
mats, xcp_data = ViconReader.loadXCP(xcp_filename)
camera_ids = [int(x['DEVICEID']) for x in xcp_data]
print 'loading 2d'
x2d_dict = ViconReader.loadX2D(x2d_filename)
x2d_frames = x2d_dict['frames']
cameras_info = ViconReader.extractCameraInfo(x2d_dict)
print 'num frames', len(x2d_frames)
Ps = [m[2] / (m[0][0, 0]) for m in mats]
track3d = Label.Track3D(mats)
primitives = QGLViewer.makePrimitives(vertices=[], altVertices=[])
primitives2D = QGLViewer.makePrimitives2D(([], [0]))
global g_all_skels, md
directory = os.path.join(os.environ['GRIP_DATA'], '151110')
_, orn_skel_dict = IO.load(os.path.join(directory, 'orn.skel'))
movie_fn = os.path.join(directory, '50_Grip_RoomCont_AA_02.v2.mov')
md = MovieReader.open_file(movie_fn,
audio=True,
frame_offset=0,
volume_ups=10)
asf_filename = os.path.join(directory, 'Martha.asf')
amc_filename = os.path.join(directory, 'Martha.amc')
asf_dict = ASFReader.read_ASF(asf_filename)
mar_skel_dict = ASFReader.asfDict_to_skelDict(asf_dict)
mar_skel_dict['anim_dict'] = ASFReader.read_AMC(amc_filename, asf_dict)
for k in ('geom_Vs', 'geom_vsplits', 'geom_Gs'):
mar_skel_dict[k] = orn_skel_dict[k].copy()
mar_skel_dict['shape_weights'] = orn_skel_dict['shape_weights']
mar_skel_dict['geom_dict'] = orn_skel_dict['geom_dict']
orn_vss = ViconReader.loadVSS(os.path.join(directory, 'Orn.vss'))
orn_vss_chan_mapping = [
orn_vss['chanNames'].index(n) for n in orn_skel_dict['chanNames']
]
orn_anim_dict = orn_skel_dict['anim_dict']
orn_vss_anim = np.zeros(
(orn_anim_dict['dofData'].shape[0], orn_vss['numChans']),
dtype=np.float32)
orn_vss_anim[:, orn_vss_chan_mapping] = orn_anim_dict['dofData']
orn_anim_dict['dofData'] = orn_vss_anim
orn_vss['anim_dict'] = orn_anim_dict
for x in [
'geom_dict', 'geom_Vs', 'geom_vsplits', 'geom_Gs', 'shape_weights'
]:
orn_vss[x] = orn_skel_dict[x]
orn_skel_dict = orn_vss
g_all_skels = {}
orn_mesh_dict, orn_skel_mesh, orn_geom_mesh = orn_t = Character.make_geos(
orn_skel_dict)
g_all_skels['orn'] = (orn_skel_dict, orn_t)
orn_skel_dict['chanValues'][:] = 0
Character.updatePoseAndMeshes(orn_skel_dict, orn_skel_mesh, orn_geom_mesh)
mar_mesh_dict, mar_skel_mesh, mar_geom_mesh = mar_t = Character.make_geos(
mar_skel_dict)
g_all_skels['mar'] = (mar_skel_dict, mar_t)
#ted_mesh_dict, ted_skel_mesh, ted_geom_mesh = ted_t = Character.make_geos(ted_skel_dict)
#g_all_skels['ted'] = (ted_skel_dict, ted_t)
#ted_skel_dict['chanValues'][0] += 1000
#Character.updatePoseAndMeshes(ted_skel_dict, ted_skel_mesh, ted_geom_mesh)
mnu = orn_skel_dict['markerNamesUnq']
mns = orn_skel_dict['markerNames']
effectorLabels = np.array([mnu.index(n) for n in mns], dtype=np.int32)
orn_graph = Label.graph_from_skel(orn_skel_dict, mnu)
boot = -10
track_orn = Label.TrackModel(orn_skel_dict, effectorLabels, mats)
#ted = GLSkel(ted_skel_dict['Bs'], ted_skel_dict['Gs']) #, mvs=ted_skel_dict['markerOffsets'], mvis=ted_skel_dict['markerParents'])
#ted = GLSkeleton(ted_skel_dict['jointNames'],ted_skel_dict['jointParents'], ted_skel_dict['Gs'][:,:,3])
#ted.setName('ted')
#ted.color = (1,1,0)
#orn = GLSkeleton(orn_skel_dict['jointNames'],orn_skel_dict['jointParents'], orn_skel_dict['Gs'][:,:,3])
#orn.setName('orn')
#orn.color = (0,1,1)
#square = GLMeshes(names=['square'],verts=[[[0,0,0],[1000,0,0],[1000,1000,0],[0,1000,0]]],vts=[[[0,0],[1,0],[1,1],[0,1]]],faces=[[[0,1,2,3]]],fts=[[[0,1,2,3]]])
#square.setImageData(np.array([[[0,0,0],[255,255,255]],[[255,255,255],[0,0,0]]],dtype=np.uint8))
#orn_geom_mesh.setImageData(np.array([[[0,0,0],[255,255,255]],[[255,255,255],[0,0,0]]],dtype=np.uint8))
P = Calibrate.composeP_fromData((60.8, ), (-51.4, 14.7, 3.2),
(6880, 2860, 5000),
0) # roughed in camera for 151110
ks = (0.06, 0.0)
mat = Calibrate.makeMat(P, ks, (1080, 1920))
orn_mapper = Opengl.ProjectionMapper(mat)
orn_mapper.setGLMeshes(orn_geom_mesh)
orn_geom_mesh.setImage((md['vbuffer'], (md['vheight'], md['vwidth'], 3)))
mar_mapper = Opengl.ProjectionMapper(mat)
mar_mapper.setGLMeshes(mar_geom_mesh)
mar_geom_mesh.setImage((md['vbuffer'], (md['vheight'], md['vwidth'], 3)))
global g_screen
g_screen = Opengl.make_quad_distortion_mesh()
QGLViewer.makeViewer(mat=mat,md=md,layers = {\
#'ted':ted, 'orn':orn,
#'ted_skel':ted_skel_mesh,'ted_geom':ted_geom_mesh,\
#'square':square,
'orn_skel':orn_skel_mesh,'orn_geom':orn_geom_mesh,\
'mar_skel':mar_skel_mesh,'mar_geom':mar_geom_mesh,\
},
primitives=primitives, primitives2D=primitives2D, timeRange=(0, len(x2d_frames) - 1, 4, 25.0), callback=intersectRaysCB, mats=mats,camera_ids=camera_ids)
def intersectRaysCB(fi):
global x2d_frames, mats, Ps, c3d_frames, view, primitives, primitives2D, track3d, prev_frame, track_orn, orn_graph, boot, g_all_skels, md, orn_mapper, mar_mapper
skipping = prev_frame is None or np.abs(fi - prev_frame) > 10
prev_frame = fi
view = QApp.view()
points, altpoints = primitives
g2d = primitives2D[0]
frame = x2d_frames[fi]
x2ds_data, x2ds_splits = ViconReader.frameCentroidsToDets(frame, mats)
g2d.setData(x2ds_data, x2ds_splits)
if skipping:
x3ds, x3ds_labels = track3d.boot(x2ds_data, x2ds_splits)
#trackGraph = Label.TrackGraph()
boot = -10
else:
x3ds, x3ds_labels = track3d.push(x2ds_data, x2ds_splits)
if False:
boot = boot + 1
if boot == 0:
x2d_threshold_hash = 0.01
penalty = 10.0 # the penalty for unlabelled points. this number should be about 10. to force more complete labellings, set it higher.
maxHyps = 500 # the number of hypotheses to maintain.
print "booting:"
numLabels = len(orn_graph[0])
l2x = -np.ones(numLabels, dtype=np.int32)
label_score = ISCV.label_from_graph(x3ds, orn_graph[0],
orn_graph[1], orn_graph[2],
orn_graph[3], maxHyps, penalty,
l2x)
clouds = ISCV.HashCloud2DList(x2ds_data, x2ds_splits,
x2d_threshold_hash)
which = np.array(np.where(l2x != -1)[0], dtype=np.int32)
pras_score, x2d_labels, vels = Label.project_assign(
clouds,
x3ds[l2x[which]],
which,
Ps,
x2d_threshold=x2d_threshold_hash)
print fi, label_score, pras_score
labelled_x3ds = x3ds[l2x[which]]
print track_orn.bootPose(x2ds_data, x2ds_splits, x2d_labels)
if boot > 0:
track_orn.push(x2ds_data, x2ds_splits, its=4)
#x3ds,x2ds_labels = Recon.intersect_rays(x2ds_data, x2ds_splits, Ps, mats, seed_x3ds = None)
points.setData(x3ds)
if c3d_frames != None:
c3ds = c3d_frames[(fi - 832) / 2]
true_labels = np.array(np.where(c3ds[:, 3] == 0)[0], dtype=np.int32)
x3ds_true = c3ds[true_labels, :3]
altpoints.setData(x3ds_true)
ci = view.cameraIndex() - 1
if True: #ci == -1:
MovieReader.readFrame(md, seekFrame=max((fi - 14) / 4, 0))
QApp.app.refreshImageData()
(orn_skel_dict, orn_t) = g_all_skels['orn']
orn_mesh_dict, orn_skel_mesh, orn_geom_mesh = orn_t
orn_anim_dict = orn_skel_dict['anim_dict']
orn_skel_dict['chanValues'][:] = orn_anim_dict['dofData'][fi]
Character.updatePoseAndMeshes(orn_skel_dict, orn_skel_mesh, orn_geom_mesh)
(mar_skel_dict, mar_t) = g_all_skels['mar']
mar_anim_dict = mar_skel_dict['anim_dict']
mar_mesh_dict, mar_skel_mesh, mar_geom_mesh = mar_t
Character.updatePoseAndMeshes(mar_skel_dict, mar_skel_mesh, mar_geom_mesh,
mar_anim_dict['dofData'][fi])
from PIL import Image
#orn_geom_mesh.setImage((md['vbuffer'],(md['vheight'],md['vwidth'],3)))
#orn_geom_mesh.refreshImage()
w, h = 1024, 1024
cam = view.cameras[0]
cam.refreshImageData(view)
aspect = float(max(1, cam.bindImage.width())) / float(
cam.bindImage.height()) if cam.bindImage is not None else 1.0
orn_mapper.project(orn_skel_dict['geom_Vs'], aspect)
data = Opengl.renderGL(w, h, orn_mapper.render, cam.bindId)
orn_geom_mesh.setImage(data)
mar_mapper.project(mar_skel_dict['geom_Vs'], aspect)
data = Opengl.renderGL(w, h, mar_mapper.render, cam.bindId)
mar_geom_mesh.setImage(data)
#image = Image.fromstring(mode='RGB', size=(w, h), data=data)
#image = image.transpose(Image.FLIP_TOP_BOTTOM)
#image.save('screenshot.png')
if 0:
global g_screen
image = Opengl.renderGL(1920, 1080, Opengl.quad_render,
(cam.bindId, g_screen))
import pylab as pl
pl.imshow(image)
pl.show()
view.updateGL()
ted_dir = os.path.join(os.environ['GRIP_DATA'], 'ted')
asf_filename = os.path.join(ted_dir, '32_Quad_Dialogue_01.asf')
amc_filename = os.path.join(ted_dir, '32_Quad_Dialogue_01.amc')
xcp_filename = os.path.join(ted_dir, '32_Quad_Dialogue_01.xcp')
skelFilename = os.path.join(ted_dir, 'ted.skel')
animFilename = os.path.join(ted_dir, 'ted.anim')
try:
ted_skel = IO.load(skelFilename)[1]
ted_anim = IO.load(animFilename)[1]
except:
print 'generating ted skel and anim'
ASFReader.convertASFAMC_to_SKELANIM(asf_filename, amc_filename,
skelFilename, animFilename)
ted_skel = IO.load(skelFilename)[1]
ted_anim = IO.load(animFilename)[1]
ted_xcp_mats, ted_xcp_data = ViconReader.loadXCP(xcp_filename)
if True: # facial animation
global ted_geom, ted_geom2, ted_shape, tony_geom, tony_shape, tony_geom2, tony_obj, ted_obj, diff_geom, c3d_frames
global tony_shape_vector, tony_shape_mat, ted_lo_rest, ted_lo_mat, c3d_points
global md, movies
ted_dir = os.path.join(os.environ['GRIP_DATA'], 'ted')
wavFilename = os.path.join(ted_dir, '32T01.WAV')
md = MovieReader.open_file(wavFilename)
c3d_filename = os.path.join(
ted_dir, '201401211653-4Pico-32_Quad_Dialogue_01_Col_wip_02.c3d')
c3d_dict = C3D.read(c3d_filename)
c3d_frames, c3d_fps, c3d_labels = c3d_dict['frames'], c3d_dict[
'fps'], c3d_dict['labels']