def check_regions_and_pairs():
"""
Make sure the tracking regions and camera pairs are well defined.
"""
regions_dict = file_tools.read_tracking_2d_regions()
camera_pairs_dict = file_tools.read_tracking_2d_camera_pairs()
region_tools.check_regions_and_camera_pairs(regions_dict, camera_pairs_dict)
def get_camera_pairs_dict():
camera_pairs = file_tools.read_tracking_2d_camera_pairs()
camera_pairs_dict = {}
for region, pairs_list in camera_pairs.iteritems():
pair_name_list = []
for pair in pairs_list:
pair_name = '{0}_{1}'.format(pair[0], pair[1])
pair_name_list.append(pair_name)
if pair_name_list:
camera_pairs_dict[region] = pair_name_list
return camera_pairs_dict
def __init__(self):
self.regions_dict = file_tools.read_tracking_2d_regions()
self.camera_pairs_dict = file_tools.read_tracking_2d_camera_pairs()
# Create dictionaries describing tranformation setup
self._create_camera_to_region_dict()
self._create_tracking_plane_to_region_dict()
self._create_region_to_anchor_plane_dict()
self._create_tracking_to_anchor_plane_dict()
self._create_camera_to_image_size_dict()
self._get_stitching_params()
# Create transformation dictionaries
self._create_tracking_plane_to_transform_dict()
self._create_camera_to_transform_dict()
def transform_2d_calibrator_nodes_ready():
"""
Returns True if the transform 2d calibrator nodes are ready. They are ready
if the number of transform 2d calibrator nodes are eqaul to the number of
camera pairs.
"""
# Get list of currently running transform 2d calibrators
calibrator_list = get_transform_2d_calibrator_nodes()
# Get list of all camera pairs
camera_pairs_dict = file_tools.read_tracking_2d_camera_pairs()
all_pairs_list = []
for pairs_list in camera_pairs_dict.values():
all_pairs_list.extend(pairs_list)
if len(all_pairs_list) == len(calibrator_list):
return True
else:
return False
def setup_redis_db():
# Create db and add empty camera assignment
db = redis.Redis('localhost',db=config.redis_db)
# Add mjpeg information
mjpeg_info_dict = mjpeg_servers.get_mjpeg_info_dict()
redis_tools.set_dict(db,'mjpeg_info_dict', mjpeg_info_dict)
# Add camera pairs information
camera_pairs_dict = file_tools.read_tracking_2d_camera_pairs()
redis_tools.set_dict(db,'camera_pairs_dict', camera_pairs_dict)
# Add external network interface
machine_def = mct_introspection.get_machine_def()
ip_iface_ext = iface_tools.get_ip_addr(machine_def['mct_master']['iface-ext'])
redis_tools.set_str(db,'ip_iface_ext',ip_iface_ext)
# Add default scale for image view
scale_default = config.camera_view_table['scale_default']
redis_tools.set_str(db,'scale', scale_default)
return db
print(t1)
print(t2)
print()
print(m1)
print()
print(m2)
print()
print(m22)
print()
print(m3)
print()
print(m33)
print()
if 0:
camera_pairs_dict = file_tools.read_tracking_2d_camera_pairs()
camera_pairs_list = camera_pairs_dict['maze']
tf_digraph = create_transform_digraph(camera_pairs_list)
print('nodes:')
print(tf_digraph.nodes())
print()
print('edges:')
print(tf_digraph.edges())
print()
m1 = get_transform_matrix(tf_digraph, 'tracking_plane_1',
'tracking_plane_1')
m2 = get_transform_matrix(tf_digraph, 'tracking_plane_1',
'tracking_plane_1')
m1_m2 = numpy.dot(m1, m2)
print(m1)
print(m2)
