def once():
global depth, rgb
preview.canvas.SetCurrent()
opennpy.sync_update()
depth,_ = opennpy.sync_get_depth()
rgb,_ = opennpy.sync_get_video()
main.update_frame(depth, rgb)
blockdraw.clear()
#blockdraw.show_grid('o1', main.occvac.occ, color=np.array([1,1,0,1]))
if 'RGB' in stencil.__dict__:
blockdraw.show_grid('occ', grid.occ, color=grid.color)
else:
blockdraw.show_grid('occ', grid.occ, color=np.array([1,0.6,0.6,1]))
preview.clearcolor=[0,0,0,0]
preview.flag_drawgrid = True
if 'R_correct' in main.__dict__:
preview.modelmat = main.R_display
else:
preview.modelmat = main.R_aligned
preview.Refresh()
window.Refresh()
pylab.waitforbuttonpress(0.005)
def once():
global depth, rgb
if not FOR_REAL:
dataset.advance()
depth = dataset.depth
rgb = dataset.rgb
else:
opennpy.sync_update()
depth,_ = opennpy.sync_get_depth()
rgb,_ = opennpy.sync_get_video()
def from_rect(m,rect):
(l,t),(r,b) = rect
return m[t:b,l:r]
global mask, rect, modelmat
try:
(mask,rect) = preprocess.threshold_and_mask(depth,config.bg)
except IndexError:
return
cv.ShowImage('mask',mask.astype('u1')*255)
global label_image
label_image = classify.predict(depth)
cv.ShowImage('label_image', ((label_image[0]+1)*100*mask).astype('u1'))
pylab.waitforbuttonpress(0.03)
def once():
global depth, rgb
if not FOR_REAL:
dataset.advance()
depth = dataset.depth
rgb = dataset.rgb
else:
opennpy.sync_update()
depth, _ = opennpy.sync_get_depth()
rgb, _ = opennpy.sync_get_video()
main.update_frame(depth, rgb)
blockdraw.clear()
if 'RGB' in stencil.__dict__:
blockdraw.show_grid('occ', grid.occ, color=grid.color)
else:
blockdraw.show_grid('occ', grid.occ, color=np.array([1, 0.6, 0.6, 1]))
window.clearcolor = [0, 0, 0, 0]
window.flag_drawgrid = True
if 'R_correct' in main.__dict__:
window.modelmat = main.R_display
g = blockcraft.translated_rotated(main.R_correct, grid.occ)
talk_to_minecraft(g)
window.Refresh()
pylab.waitforbuttonpress(0.005)
import sys
sys.stdout.flush()
def record(filename=None):
opennpy.align_depth_to_rgb()
if filename is None:
filename = str(np.random.rand())
foldername = 'data/sets/%s/' % filename
dataset.folder = foldername
os.mkdir(foldername)
shutil.copytree('data/newest_calibration/config', '%s/config' % foldername)
print "Created new dataset: %s" % foldername
frame = 0
try:
while 1:
opennpy.sync_update()
(depth, _) = opennpy.sync_get_depth()
(rgb, _) = opennpy.sync_get_video()
np.save('%s/depth_%05d.npy' % (foldername, frame), depth)
cv.CvtColor(rgb, rgb, cv.CV_RGB2BGR)
cv.SaveImage('%s/rgb_%05d.png' % (foldername, frame), rgb)
if frame % 30 == 0:
print 'frame: %d' % frame
frame = frame + 1
except KeyboardInterrupt:
print "Captured %d frames" % frame
compress()
def once():
global depth, rgb
if not FOR_REAL:
dataset.advance()
depth = dataset.depth
rgb = dataset.rgb
else:
opennpy.sync_update()
depth,_ = opennpy.sync_get_depth()
rgb,_ = opennpy.sync_get_video()
def from_rect(m,rect):
(l,t),(r,b) = rect
return m[t:b,l:r]
global mask, rect, modelmat
try:
(mask,rect) = preprocess.threshold_and_mask(depth,config.bg)
except IndexError:
return
cv.ShowImage('mask',mask.astype('u1')*255)
global label_image
label_image = classify.predict(depth)
cv.ShowImage('label_image', ((label_image[0]+1)*100*mask).astype('u1'))
pylab.waitforbuttonpress(0.03)
def record(filename=None):
opennpy.align_depth_to_rgb()
if filename is None:
filename = str(np.random.rand())
foldername = 'data/sets/%s/' % filename
dataset.folder = foldername
os.mkdir(foldername)
shutil.copytree('data/newest_calibration/config', '%s/config' % foldername)
print "Created new dataset: %s" % foldername
frame = 0
try:
while 1:
opennpy.sync_update()
(depth,_) = opennpy.sync_get_depth()
(rgb,_) = opennpy.sync_get_video()
np.save('%s/depth_%05d.npy' % (foldername,frame), depth)
cv.CvtColor(rgb, rgb, cv.CV_RGB2BGR)
cv.SaveImage('%s/rgb_%05d.png' % (foldername,frame), rgb)
if frame % 30 == 0:
print 'frame: %d' % frame
frame = frame + 1
except KeyboardInterrupt:
print "Captured %d frames" % frame
compress()
def once():
global depth, rgb
if not FOR_REAL:
dataset.advance()
depth = dataset.depth
rgb = dataset.rgb
else:
opennpy.sync_update()
depth,_ = opennpy.sync_get_depth()
rgb,_ = opennpy.sync_get_video()
main.update_frame(depth, rgb)
blockdraw.clear()
if 'RGB' in stencil.__dict__:
blockdraw.show_grid('occ', grid.occ, color=grid.color)
else:
blockdraw.show_grid('occ', grid.occ, color=np.array([1,0.6,0.6,1]))
window.clearcolor=[0,0,0,0]
window.flag_drawgrid = True
if 'R_correct' in main.__dict__:
window.modelmat = main.R_display
g = blockcraft.translated_rotated(main.R_correct, grid.occ)
talk_to_minecraft(g)
window.Refresh()
pylab.waitforbuttonpress(0.005)
import sys
sys.stdout.flush()
def once():
global depth, rgb
if not FOR_REAL:
dataset.advance()
depth = dataset.depth
rgb = dataset.rgb
else:
opennpy.sync_update()
depth, _ = opennpy.sync_get_depth()
rgb, _ = opennpy.sync_get_video()
main.update_frame(depth, rgb)
blockdraw.clear()
try:
c, _ = hashalign.find_best_alignment(grid.occ, 0 * grid.occ,
target_model, ~target_model)
except ValueError:
pass
else:
tm = hashalign.apply_correction(target_model, *c)
tm = np.ascontiguousarray(tm)
not_filled = tm & ~grid.occ
correct = tm & grid.occ
incorrect = ~tm & grid.occ
try:
next_layer = np.min(np.nonzero(not_filled)[1])
except ValueError:
blockdraw.show_grid('0',
grid.occ,
color=np.array([0.2, 1, 0.2, 1]))
else:
blockdraw.show_grid('1', incorrect, color=np.array([1, 1, 0.1, 1]))
nf = not_filled * 0
nf[:, next_layer, :] = 1
nf = nf & not_filled
blockdraw.show_grid('2', nf, color=np.array([1, 0.2, 1.0, 1]))
blockdraw.show_grid('3',
correct,
color=np.array([0.1, 0.3, 0.1, 1]))
window.clearcolor = [0, 0, 0, 0]
window.flag_drawgrid = False
if 'R_correct' in main.__dict__:
window.modelmat = main.R_display
#show_rgb(rgb)
window.Refresh()
pylab.waitforbuttonpress(0.005)
sys.stdout.flush()
def once():
global depth, rgb
if not FOR_REAL:
dataset.advance()
depth = dataset.depth
rgb = dataset.rgb
else:
opennpy.sync_update()
depth,_ = opennpy.sync_get_depth()
rgb,_ = opennpy.sync_get_video()
main.update_frame(depth, rgb)
blockdraw.clear()
try:
c,_ = hashalign.find_best_alignment(grid.occ,0*grid.occ,
target_model,~target_model)
except ValueError:
pass
else:
tm = hashalign.apply_correction(target_model, *c)
tm = np.ascontiguousarray(tm)
not_filled = tm & ~grid.occ
correct = tm & grid.occ
incorrect = ~tm & grid.occ
try:
next_layer = np.min(np.nonzero(not_filled)[1])
except ValueError:
blockdraw.show_grid('0', grid.occ, color=np.array([0.2,1,0.2,1]))
else:
blockdraw.show_grid('1', incorrect,
color=np.array([1,1,0.1,1]))
nf = not_filled*0
nf[:,next_layer,:] = 1
nf = nf & not_filled
blockdraw.show_grid('2', nf,
color=np.array([1,0.2,1.0,1]))
blockdraw.show_grid('3', correct, color=np.array([0.1,0.3,0.1,1]))
window.clearcolor=[0,0,0,0]
window.flag_drawgrid = False
if 'R_correct' in main.__dict__:
window.modelmat = main.R_display
#show_rgb(rgb)
window.Refresh()
pylab.waitforbuttonpress(0.005)
sys.stdout.flush()
def block_once(self):
"""Process the next blockplayer frame"""
opennpy.sync_update()
depth,_ = opennpy.sync_get_depth()
rgb,_ = opennpy.sync_get_video()
main.update_frame(depth, rgb)
# Update the blocks in the playing area
if self.state < Game.STATE_CHECKWALL and self.update_blocks:
self.blocks = main.grid.occ
if hasattr(main, 'R_correct'):
self.blocks = blockcraft.translated_rotated(main.R_correct, self.blocks)
self.blocks = self.block_slice(self.blocks)
self.board.update_blocks(self.blocks,
remove=self.board.wall_abs-Board.BOARD_BORDER > Board.PLAY_WIDTH)
def once():
global depth
global rgb
opennpy.sync_update()
depth,_ = opennpy.sync_get_depth()
rgb,_ = opennpy.sync_get_video()
global x,y,z,xyz
if PREPROCESS:
global mask, rect
mask, rect = preprocess.threshold_and_mask(depth, config.bg)
(l,t),(r,b) = rect
depth_ = np.ascontiguousarray(depth[t:b,l:r])
v,u = np.mgrid[t:b,l:r].astype('f')
x,y,z = calibkinect.convertOpenNI2Real(depth_,u,v)
x=x[mask[t:b,l:r]]
y=y[mask[t:b,l:r]]
z=z[mask[t:b,l:r]]
rgb_ = rgb[t:b,l:r,:][mask[t:b,l:r],:]
else:
x,y,z = calibkinect.convertOpenNI2Real(depth)
#global X,Y,Z
#X,Y,Z = calibkinect.convertReal2OpenNI(x,y,z)
x,y,z = map(lambda _:_.flatten(), (x,y,z))
rgb_ = rgb.reshape(-1,3)
#x = x[depth>0]
#y = y[depth>0]
#z = z[depth>0]
xyz_ = np.ascontiguousarray(np.dstack((x,y,z)).reshape(-1,3))
#xyz_ = xyz - xyz.mean(0)
#xyz_ /= np.std(xyz_)
rgba = np.empty((xyz_.shape[0],4),'f')
rgba[:,3] = 1
rgba[:,:3] = rgb_.astype('f')/256.0
window.lookat = np.array([0,0,0])
window.update_points(xyz_,rgba)
window.clearcolor = [0,0,0,0]
window.Refresh()
pylab.waitforbuttonpress(0.005)
def once():
global depth
global rgb
opennpy.sync_update()
depth, _ = opennpy.sync_get_depth()
rgb, _ = opennpy.sync_get_video()
global x, y, z, xyz
if PREPROCESS:
global mask, rect
mask, rect = preprocess.threshold_and_mask(depth, config.bg)
(l, t), (r, b) = rect
depth_ = np.ascontiguousarray(depth[t:b, l:r])
v, u = np.mgrid[t:b, l:r].astype('f')
x, y, z = calibkinect.convertOpenNI2Real(depth_, u, v)
x = x[mask[t:b, l:r]]
y = y[mask[t:b, l:r]]
z = z[mask[t:b, l:r]]
rgb_ = rgb[t:b, l:r, :][mask[t:b, l:r], :]
else:
x, y, z = calibkinect.convertOpenNI2Real(depth)
#global X,Y,Z
#X,Y,Z = calibkinect.convertReal2OpenNI(x,y,z)
x, y, z = map(lambda _: _.flatten(), (x, y, z))
rgb_ = rgb.reshape(-1, 3)
#x = x[depth>0]
#y = y[depth>0]
#z = z[depth>0]
xyz_ = np.ascontiguousarray(np.dstack((x, y, z)).reshape(-1, 3))
#xyz_ = xyz - xyz.mean(0)
#xyz_ /= np.std(xyz_)
rgba = np.empty((xyz_.shape[0], 4), 'f')
rgba[:, 3] = 1
rgba[:, :3] = rgb_.astype('f') / 256.0
window.lookat = np.array([0, 0, 0])
window.update_points(xyz_, rgba)
window.clearcolor = [0, 0, 0, 0]
window.Refresh()
pylab.waitforbuttonpress(0.005)
def run_calib():
config.load('data/newest_calibration')
opennpy.align_depth_to_rgb()
samples = []
for i in arange(0,2*np.pi,np.pi/8):
line = line_through_point(center, i)
draw_line_XZ(line)
pylab.waitforbuttonpress(0.1)
for _ in range(60):
opennpy.sync_update()
rgb, _ = opennpy.sync_get_video()
depth, _ = opennpy.sync_get_depth()
samples.append((line, rgb, depth))
return samples
def once():
opennpy.sync_update()
(depth,_), (rgb,_) = opennpy.sync_get_depth(), opennpy.sync_get_video()
# Look for chessboard corners in the image
was_found, corners = cv.FindChessboardCorners(cv.fromarray(255-rgb),
checkerboard.pattern_size)
preview = cv.fromarray(rgb.copy())
if was_found:
cv.DrawChessboardCorners(preview, checkerboard.pattern_size,
corners, was_found)
cv.ShowImage("RGB", preview)
if not was_found: return
# Sample the kinect depth image X,Y,Z points at the corners
XYZ = calibkinect.convertOpenNI2Real(depth)
XYZ = [scipy.ndimage.map_coordinates(im, np.array(corners).transpose()[::-1,:],
order=0, prefilter=False) for im in XYZ]
XYZ = np.vstack(XYZ).transpose()
return XYZ
def once():
global depth, rgb
if not FOR_REAL:
dataset.advance()
depth = dataset.depth
rgb = dataset.rgb
else:
opennpy.sync_update()
depth,_ = opennpy.sync_get_depth()
rgb,_ = opennpy.sync_get_video()
main.update_frame(depth, rgb)
blockdraw.clear()
blockdraw.show_grid('o1', main.occvac.occ, color=np.array([1,1,0,1]))
if 'RGB' in stencil.__dict__:
blockdraw.show_grid('occ', grid.occ, color=grid.color)
else:
blockdraw.show_grid('occ', grid.occ, color=np.array([1,0.6,0.6,1]))
#blockdraw.show_grid('vac', grid.vac,
# color=np.array([0.6,1,0.6,0]))
if 0 and lattice.is_valid_estimate():
window.clearcolor=[0.9,1,0.9,0]
else:
window.clearcolor=[0,0,0,0]
#window.clearcolor=[1,1,1,0]
window.flag_drawgrid = True
if 1:
update_display()
if 'R_correct' in main.__dict__:
window.modelmat = main.R_display
show_rgb(rgb)
window.Refresh()
pylab.waitforbuttonpress(0.005)
sys.stdout.flush()
def once():
global depth, rgb
if not FOR_REAL:
dataset.advance()
depth = dataset.depth
rgb = dataset.rgb
else:
opennpy.sync_update()
depth, _ = opennpy.sync_get_depth()
rgb, _ = opennpy.sync_get_video()
main.update_frame(depth, rgb)
blockdraw.clear()
#blockdraw.show_grid('o1', main.occvac.occ, color=np.array([1,1,0,1]))
if 'RGB' in stencil.__dict__:
blockdraw.show_grid('occ', grid.occ, color=grid.color)
else:
blockdraw.show_grid('occ', grid.occ, color=np.array([1, 0.6, 0.6, 1]))
#blockdraw.show_grid('vac', grid.vac,
# color=np.array([0.6,1,0.6,0]))
if 0 and lattice.is_valid_estimate():
window.clearcolor = [0.9, 1, 0.9, 0]
else:
window.clearcolor = [0, 0, 0, 0]
#window.clearcolor=[1,1,1,0]
window.flag_drawgrid = True
if 1:
update_display()
if 'R_correct' in main.__dict__:
window.modelmat = main.R_display
#show_rgb(rgb)
window.Refresh()
pylab.waitforbuttonpress(0.005)
sys.stdout.flush()
def run_calib():
close('all')
"""Run the table plane calibration
"""
global points, depth
print("Getting an image from the camera")
opennpy.align_depth_to_rgb()
for i in range(10):
opennpy.sync_update()
depth, _ = opennpy.sync_get_depth()
rgb, _ = opennpy.sync_get_video()
fig = figure(1)
clf()
points = []
def pick(event):
global points
points.append((event.xdata, event.ydata))
print('Picked point %d of 4' % (len(points)))
#imshow(depth)
#imshow(1./depth)
imshow(rgb*np.dstack(3*[1./depth]))
draw()
fig.canvas.mpl_disconnect('button_press_event')
fig.canvas.mpl_connect('button_press_event', pick)
print("Click four points")
while len(points) < 4:
waitforbuttonpress(0.001)
print 'OK'
np.save('%s/config/boundpts' % (newest_folder), points)
np.save('%s/config/depth' % (newest_folder), depth)
finish_table_calib()
def run_calib():
close('all')
"""Run the table plane calibration
"""
global points, depth
print("Getting an image from the camera")
opennpy.align_depth_to_rgb()
for i in range(10):
opennpy.sync_update()
depth, _ = opennpy.sync_get_depth()
rgb, _ = opennpy.sync_get_video()
fig = figure(1)
clf()
points = []
def pick(event):
global points
points.append((event.xdata, event.ydata))
print('Picked point %d of 4' % (len(points)))
#imshow(depth)
#imshow(1./depth)
imshow(rgb * np.dstack(3 * [1. / depth]))
draw()
fig.canvas.mpl_disconnect('button_press_event')
fig.canvas.mpl_connect('button_press_event', pick)
print("Click four points")
while len(points) < 4:
waitforbuttonpress(0.001)
print 'OK'
np.save('%s/config/boundpts' % (newest_folder), points)
np.save('%s/config/depth' % (newest_folder), depth)
finish_table_calib()
def record(filename=None, cams=(0,), do_rgb=False):
if len(cams) > 1 and do_rgb:
print """You're trying to record from 2+ kinects with RGB and depth.
This probably will not work out for you, but it depends on if you have
enough USB bandwidth to support all four streams. Call record with
do_rgb=False to turn off rgb."""
q = multiprocessing.Queue(10000)
p = multiprocessing.Process(target=worker, args=(q,))
p.start()
opennpy.align_depth_to_rgb()
if filename is None:
filename = str(time.time())
foldername = KINECT_PATH + '%s' % filename
dataset.folder = foldername
try:
os.makedirs(foldername)
except OSError:
pass
#shutil.copytree('data/newest_calibration/config', '%s/config' % foldername)
print "Created new dataset: %s" % foldername
min_delay = 1
frame = 0
frame_md5s = {}
frame_last_update = {}
def check_frame(name, cam, frame_data):
frame_md5 = hashlib.md5(frame_data).digest()
key = '%s:%d' % (name, cam)
if frame_md5s.get(key) == frame_md5:
#print('Kinect [%s] is repeating data, likely crashed...' % key)
last_update = frame_last_update.get(key)
if last_update is None or (time.time() - last_update) > 10.:
return 'die'
else:
frame_last_update[key] = time.time()
frame_md5s[key] = frame_md5
return 'new'
def die():
q.put(None)
while 1:
print('')
st = time.time()
opennpy.sync_update()
for cam in cams:
(depth,_) = opennpy.sync_get_depth(cam)
ret = check_frame('depth', cam, depth.tostring())
if ret == 'die':
return die()
elif ret == 'new':
q.put(('%s/depth_%f_%05d_%d.snappy' % (foldername,st,frame,cam), depth.tostring()))
if do_rgb:
(rgb,_) = opennpy.sync_get_video(cam)
ret = check_frame('rgb', cam, rgb.tostring())
if ret == 'die':
return die()
elif ret == 'new':
rgb = cv2.cvtColor(rgb, cv.CV_RGB2BGR)
q.put(('%s/rgb_%f_%05d_%d.ppm' % (foldername,st,frame,cam), rgb))
if frame % 30 == 0:
print 'frame: %d' % frame
cur_time = time.time()
print({k: cur_time - v for k, v in frame_last_update.items()})
frame = frame + 1
sleep_time = max(0, min_delay - (time.time() - st))
#time.sleep(sleep_time)
print('Time: %f' % (time.time() - st,))
import opennpy a = opennpy.sync_get_depth() b = opennpy.sync_get_video() opennpy.align_depth_to_rgb() a = opennpy.sync_get_depth() b = opennpy.sync_get_video()
def get_video():
return frame_convert.video_cv(opennpy.sync_get_video()[0])
def show_video():
cv.ShowImage('Video', frame_convert.video_cv(opennpy.sync_get_video()[0]))
def get_video():
return opennpy.sync_get_video()[0]
