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 start(dset=None, frame_num=0):
main.initialize()
if not FOR_REAL:
if dset is None:
dataset.load_random_dataset()
else:
dataset.load_dataset(dset)
while dataset.frame_num < frame_num:
dataset.advance()
name = dset
name = os.path.split(name)[1]
custom = os.path.join('data/sets/', name, 'gt.txt')
if os.path.exists(custom):
# Try dataset directory first
fname = custom
else:
import re
# Fall back on generic ground truth file
match = re.match('.*_z(\d)m_(.*)', name)
number = int(match.groups()[0])
fname = 'data/experiments/gt/gt%d.txt' % number
with open(fname) as f:
GT = grid.gt2grid(f.read())
grid.initialize_with_groundtruth(GT)
else:
config.load('data/newest_calibration')
opennpy.align_depth_to_rgb()
dataset.setup_opencl()
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()
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)
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):
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 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()
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)
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 start(dset=None, frame_num=0):
main.initialize()
if not FOR_REAL:
if dset is None:
dataset.load_random_dataset()
else:
dataset.load_dataset(dset)
while dataset.frame_num < frame_num:
dataset.advance()
name = dset
name = os.path.split(name)[1]
custom = os.path.join('data/sets/', name, 'gt.txt')
if os.path.exists(custom):
# Try dataset directory first
fname = custom
else:
import re
# Fall back on generic ground truth file
match = re.match('.*_z(\d)m_(.*)', name)
number = int(match.groups()[0])
fname = 'data/experiments/gt/gt%d.txt' % number
with open(fname) as f:
GT = grid.gt2grid(f.read())
grid.initialize_with_groundtruth(GT)
else:
config.load('data/newest_calibration')
opennpy.align_depth_to_rgb()
dataset.setup_opencl()
def preview(cams):
opennpy.align_depth_to_rgb()
opennpy.sync_update()
global depth_cache
for cam in cams:
(depth,_) = opennpy.sync_get_depth(cam)
print(depth.shape)
print "Depth aligned:", is_aligned(depth)
depth_cache.append(np.array(depth))
depth_cache = depth_cache[-6:]
show_depth('depth_%d'%cam, depth)
def start(dset=None, frame_num=0):
main.initialize()
if not FOR_REAL:
if dset is None:
dataset.load_random_dataset()
else:
dataset.load_dataset(dset)
while dataset.frame_num < frame_num:
dataset.advance()
else:
config.load('data/newest_calibration')
opennpy.align_depth_to_rgb()
dataset.setup_opencl()
def block_setup(self):
"""Initialize blockplayer stuff"""
glxcontext.makecurrent()
main.initialize()
config.load('data/newest_calibration')
opennpy.align_depth_to_rgb()
dataset.setup_opencl()
self.blocks = None
self.block_loop_quit = False
self.block_initialized = True
self.block_loop()
def start(dset=None, frame_num=0):
main.initialize()
if not FOR_REAL:
if dset is None:
dataset.load_random_dataset()
else:
dataset.load_dataset(dset)
while dataset.frame_num < frame_num:
dataset.advance()
else:
config.load('data/newest_calibration')
opennpy.align_depth_to_rgb()
dataset.setup_opencl()
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 start(dset=None, frame_num=0):
main.initialize()
#with open('data/experiments/collab/2011.txt') as f:
global target_model
with open('data/experiments/collab/block.txt') as f:
target_model = grid.gt2grid(f.read())
#grid.initialize_with_groundtruth(GT)
if not FOR_REAL:
if dset is None:
dataset.load_random_dataset()
else:
dataset.load_dataset(dset)
while dataset.frame_num < frame_num:
dataset.advance()
else:
config.load('data/newest_calibration')
opennpy.align_depth_to_rgb()
dataset.setup_opencl()
def start():
main.initialize()
config.load('data/newest_calibration')
opennpy.align_depth_to_rgb()
dataset.setup_opencl()
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 numpy as np
import pylab
import opennpy
from blockplayer import calibkinect
from blockplayer import config
from blockplayer import preprocess
if config.ALIGNED:
opennpy.align_depth_to_rgb()
from blockplayer.visuals.pointwindow import PointWindow
global window
if not 'window' in globals():
window = PointWindow(title='demo_calib', size=(640,480))
mat = np.linalg.inv(calibkinect.aligned_projection())
mat = np.ascontiguousarray(mat)
PREPROCESS = True
def once():
global depth
global rgb
opennpy.sync_update()
depth,_ = opennpy.sync_get_depth()
rgb,_ = opennpy.sync_get_video()
global x,y,z,xyz
def go(cams=(0,)):
opennpy.align_depth_to_rgb()
while 1:
preview(cams)
pylab.waitforbuttonpress(0.005)
from OpenGL.GL import *
from OpenGL.GLUT import *
import numpy as np
from rtmodel import mesh
from rtmodel import camera
from wxpy3d import Window
from wxpy3d.opengl_state import opengl_state
import opennpy
import calibkinect
import cv
import scipy.ndimage
import os
import cPickle as pickle
opennpy.align_depth_to_rgb(); opennpy.sync_update()
np.set_printoptions(2)
"""
My best guess for the intrinsic calibration values for the dell projector are:
KK = [[2460, 0, 1152/2],
[0, 2460, 863],
[0, 0, 1]]
This is based on measuring the focal length with a tape measure, averaging
between my measurements for X and Y. Assume the principal point is at the bottom
and pixels are square.
"""
if not 'window' in globals():
def go():
opennpy.align_depth_to_rgb()
while 1:
preview()
pylab.waitforbuttonpress(0.005)
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()
