def main():
p = optparse.OptionParser(usage="Usage: %prog [ options ] <xres> <yres>\n"
"This program displays a live image of your camera")
add_common_options(p)
p.add_option("-o", "--offset", default = "0x0", dest="offset",
help="Offset in pixels [%default]")
p.add_option("-b", "--color-coding", default="Y8", dest="cc",
help="Color coding for acquistion [%default]")
options, args = p.parse_args()
if len(args) != 2:
p.error("Need x and y resolution!")
l = DC1394Library()
cam = handle_common_options(options,l)
m, = filter(lambda m: m.name == "FORMAT7_0", cam.modes)
cam.mode = m
size = map(int, args)
offset = map(int, options.offset.split('x'))
cc = options.cc
m.setup(size, offset, cc)
if cam:
app = QApplication(args)
w1 = LiveCameraWin(cam); w1.show(); w1.raise_()
sys.exit(app.exec_())
def main():
p = optparse.OptionParser(usage="Usage: %prog [ options ]\n"
"Acquires 25 pictures and exits.")
add_common_options(p)
options, args = p.parse_args()
l = DC1394Library()
cam = handle_common_options(options,l)
if cam:
print "Starting camera in normal mode. We need to process all pictures!"
cam.start(interactive=False)
print "Better be quick now! All images are saved in a Queue object, if we"
print "are not fast enough in acquisition, the queue will overrun and"
print "the program will crash."
print "Acquiring 25 images"
for idx in range(1,26):
i = cam.shot()
print "The last picture %i was acquired at: " % idx, i.timestamp
cam.stop()
print "All done."
def main():
p = optparse.OptionParser(
usage="Usage: %prog [ options ]\n" "This program lets the camera run in free running mode."
)
add_common_options(p)
options, args = p.parse_args()
l = DC1394Library()
cam = handle_common_options(options, l)
if cam:
print "Starting camera in free running mode!"
cam.start(interactive=True)
print "We can now do whatever we want, the camera is acquiring"
print "frames in the background in another thread. Let's sleep a while"
for i in range(10, -1, -1):
print i
time.sleep(1)
print "The last picture was acquired at: ", cam.current_image.timestamp
cam.stop()
print "All done."
def main():
"""
Parses arguments; initialises logger; initialises camera driver if
necessary; loads single image from disk if necessary; and runs desired parts
of pipeline, or loads output from previous execution for printout.
"""
options, args = argparse.run()
loginit.run(options.verbosity)
logger = logging.getLogger('main')
logger.info(' '.join(sys.argv[1:]))
if options.simulate == 0:
options.simulate = None
l = DC1394Library()
elif options.simulate > 0:
options.simulate -= 1
elif options.simtime is None:
options.simtime = 36000
global pipeline
pipeline = Pipeline(options)
if options.disk:
logger.info('using poses from disk')
pipe = Pipeline()
pipe.options = options
printer = Printer(pipe=pipe)
printer.final()
logger.info('done. exiting')
sys.exit(0)
if args:
try:
image = cv2.imread('images/' + args[0],
cv2.CV_LOAD_IMAGE_GRAYSCALE)
pipeline.set_image(image)
logger.info('opening image file %s from disk' % args[0])
except IOError:
logger.error('image file not found: %s' % args[0])
exit(1)
elif options.simulate is not None:
logger.info('running in simulation mode')
else:
try:
fwcam = handle_common_options(options, l)
pipeline.set_fwcam(fwcam)
logger.info('init. pydc1394 camera object')
logger.info('camera: %s' % fwcam.model)
logger.info('mode: %s' % fwcam.mode)
logger.info('framerate: %d' % fwcam.framerate.val)
except:
logger.error('unable to open camera capture')
exit(1)
pipeline.run()
def main():
"""
Parses arguments; initialises logger; initialises camera driver if
necessary; loads single image from disk if necessary; and runs desired parts
of pipeline, or loads output from previous execution for printout.
"""
options, args = argparse.run()
loginit.run(options.verbosity)
logger = logging.getLogger('main')
logger.info(' '.join(sys.argv[1:]))
if options.simulate == 0:
options.simulate = None
l = DC1394Library()
elif options.simulate > 0:
options.simulate -= 1
elif options.simtime is None:
options.simtime = 36000
global pipeline
pipeline = Pipeline(options)
if options.disk:
logger.info('using poses from disk')
pipe = Pipeline()
pipe.options = options
printer = Printer(pipe=pipe)
printer.final()
logger.info('done. exiting')
sys.exit(0)
if args:
try:
image = cv2.imread('images/'+args[0], cv2.CV_LOAD_IMAGE_GRAYSCALE)
pipeline.set_image(image)
logger.info('opening image file %s from disk' % args[0])
except IOError:
logger.error('image file not found: %s' % args[0])
exit(1)
elif options.simulate is not None:
logger.info('running in simulation mode')
else:
try:
fwcam = handle_common_options(options, l)
pipeline.set_fwcam(fwcam)
logger.info('init. pydc1394 camera object')
logger.info('camera: %s' % fwcam.model)
logger.info('mode: %s' % fwcam.mode)
logger.info('framerate: %d' % fwcam.framerate.val)
except:
logger.error('unable to open camera capture')
exit(1)
pipeline.run()
def main():
p = optparse.OptionParser(usage="Usage: %prog [ options ]\n"
"This program displays a live image of your camera")
add_common_options(p)
options, args = p.parse_args()
l = DC1394Library()
cam = handle_common_options(options,l)
if cam:
app = QApplication(args)
w1 = LiveCameraWin(cam); w1.show(); w1.raise_()
sys.exit(app.exec_())
def main():
p = optparse.OptionParser(usage="Usage: %prog [ options ]\n"
"This program displays a live image of your camera")
add_common_options(p)
options, args = p.parse_args()
l = DC1394Library()
cam = handle_common_options(options,l)
if cam:
app = wx.PySimpleApp()
LiveCameraDisplay(cam)
app.MainLoop()
def main():
"""
See module synopsis. Passes image stream from camera driver to OpenCV's
chessboard corner finder until a threshold number of point correspondence
sets are achieved. Passes these sets to OpenCV/CalibrateCamera2, and writes
the resulting estimate for the camera intrinsics to file using Numpy's save
function.
"""
#p = optparse.OptionParser(usage="Usage: %prog [ options ]\n"
# "This program lets the camera run in free running mode.")
options, args = argparse.run()
loginit.run(options.verbosity)
logger = logging.getLogger('main')
#add_common_options(p)
l = DC1394Library()
global cam
cam = handle_common_options(options, l)
try:
cam.start(interactive = True)
except IOError:
print 'error: cannot open stream'
exit(1)
dims = (9,6)
pts_per_board = dims[0] * dims[1]
nr_samples = 20
pt_counts = np.zeros((nr_samples, 1), dtype = int) #pts per image
frame = np.asarray(cam.current_image)
model_pts = np.zeros((nr_samples * pts_per_board, 3), dtype = float)
model_pts = model_pts.astype('float32')
image_pts = np.zeros((nr_samples * pts_per_board, 2), dtype = float)
image_pts = image_pts.astype('float32')
i = 0
while i < nr_samples:
frame = np.asarray(cam.current_image)
found, points = cv2.findChessboardCorners(frame, dims, flags=cv2.CALIB_CB_FAST_CHECK)
if found and ((points.shape)[0] == pts_per_board):
cv2.drawChessboardCorners(frame, (6,9), points, found)
cv2.imshow("win2", frame)
cv2.waitKey(2)
step = i * pts_per_board
j = 0
while j < pts_per_board:
image_pts[step, 0] = points[j, 0, 0]
image_pts[step, 1] = points[j, 0, 1]
model_pts[step, 0] = float(j) / float(dims[0])
model_pts[step, 1] = float(j) % float(dims[0])
model_pts[step, 2] = 0.0
step += 1
j += 1
pt_counts[i, 0] = pts_per_board
cv2.waitKey(2)
i += 1
time.sleep(1)
else:
cv2.imshow("win2", frame)
cv2.waitKey(2)
camera_matrix = np.array([
[2.23802515e+03, 0.0, 5.89782959e+02],
[0.0, 2.07124146e+03, 4.55921570e+02],
[0.0, 0.0, 1.]
])
dist_coeffs = np.zeros(4)
np.save("image_pts.npy", image_pts)
np.save("model_pts.npy", model_pts)
success, intrinsic, distortion_coeffs, rot_est_vecs, transl_est_vecs = cv2.calibrateCamera(model_pts, image_pts, frame.shape, camera_matrix, dist_coeffs, flags=cv2.CALIB_USE_INTRINSIC_GUESS)
np.save("intrinsic.npy", intrinsic)
np.save("distortion_coeffs.npy", distortion_coeffs)
np.save("calibration_rotation_vectors.npy", rot_est_vecs)
np.save("calibration_translation_vectors.npy", transl_est_vecs)
def main():
"""
See module synopsis. Passes image stream from camera driver to OpenCV's
chessboard corner finder until a threshold number of point correspondence
sets are achieved. Passes these sets to OpenCV/CalibrateCamera2, and writes
the resulting estimate for the camera intrinsics to file using Numpy's save
function.
"""
#p = optparse.OptionParser(usage="Usage: %prog [ options ]\n"
# "This program lets the camera run in free running mode.")
options, args = argparse.run()
loginit.run(options.verbosity)
logger = logging.getLogger('main')
#add_common_options(p)
l = DC1394Library()
global cam
cam = handle_common_options(options, l)
try:
cam.start(interactive=True)
except IOError:
print 'error: cannot open stream'
exit(1)
dims = (9, 6)
pts_per_board = dims[0] * dims[1]
nr_samples = 20
pt_counts = np.zeros((nr_samples, 1), dtype=int) #pts per image
frame = np.asarray(cam.current_image)
model_pts = np.zeros((nr_samples * pts_per_board, 3), dtype=float)
model_pts = model_pts.astype('float32')
image_pts = np.zeros((nr_samples * pts_per_board, 2), dtype=float)
image_pts = image_pts.astype('float32')
i = 0
while i < nr_samples:
frame = np.asarray(cam.current_image)
found, points = cv2.findChessboardCorners(
frame, dims, flags=cv2.CALIB_CB_FAST_CHECK)
if found and ((points.shape)[0] == pts_per_board):
cv2.drawChessboardCorners(frame, (6, 9), points, found)
cv2.imshow("win2", frame)
cv2.waitKey(2)
step = i * pts_per_board
j = 0
while j < pts_per_board:
image_pts[step, 0] = points[j, 0, 0]
image_pts[step, 1] = points[j, 0, 1]
model_pts[step, 0] = float(j) / float(dims[0])
model_pts[step, 1] = float(j) % float(dims[0])
model_pts[step, 2] = 0.0
step += 1
j += 1
pt_counts[i, 0] = pts_per_board
cv2.waitKey(2)
i += 1
time.sleep(1)
else:
cv2.imshow("win2", frame)
cv2.waitKey(2)
camera_matrix = np.array([[2.23802515e+03, 0.0, 5.89782959e+02],
[0.0, 2.07124146e+03, 4.55921570e+02],
[0.0, 0.0, 1.]])
dist_coeffs = np.zeros(4)
np.save("image_pts.npy", image_pts)
np.save("model_pts.npy", model_pts)
success, intrinsic, distortion_coeffs, rot_est_vecs, transl_est_vecs = cv2.calibrateCamera(
model_pts,
image_pts,
frame.shape,
camera_matrix,
dist_coeffs,
flags=cv2.CALIB_USE_INTRINSIC_GUESS)
np.save("intrinsic.npy", intrinsic)
np.save("distortion_coeffs.npy", distortion_coeffs)
np.save("calibration_rotation_vectors.npy", rot_est_vecs)
np.save("calibration_translation_vectors.npy", transl_est_vecs)
