# Open ClickPoints Database
db = DataFileExtended("./ExampleData/sim_data.cdb", "w")
# Define ClickPoints Marker
detection_marker_type = db.setMarkerType(name="Detection_Marker",
color="#FF0000",
style='{"scale":1.2}')
db.deleteMarkers(type=detection_marker_type)
track_marker_type = db.setMarkerType(name="Track_Marker",
color="#00FF00",
mode=db.TYPE_Track)
db.deleteMarkers(type=track_marker_type)
prediction_marker_type = db.setMarkerType(name="Prediction_Marker",
color="#0000FF")
db.deleteMarkers(type=prediction_marker_type)
# Delete Old Tracks
db.deleteTracks(type=track_marker_type)
# Start Iteration over Images
db_path = db.setPath("")
print('Starting Iteration')
for i in range(T):
# Prediction step, without applied control(vector of zeros)
MultiKal.predict(i=i)
image = db.setImage("", db_path, timestamp=i)
# Detection step
SegMap = TS.detect(image.data)
X, Y = np.random.rand(0, 1, (2, N))
X *= arena_w
Y *= arena_h
print("Found %s Objects!" % len(Positions))
if db.getMarkerType(name="PT_Prediction_Marker"):
marker_type3 = db.getMarkerType(name= "PT_Prediction_Marker")
else:
marker_type3 = db.setMarkerType(name="PT_Prediction_Marker", color="#0000FF")
if db.getMarkerType(name="PT_Stitch_Marker"):
marker_type4 = db.getMarkerType(name="PT_Stitch_Marker")
else:
marker_type4 = db.setMarkerType(name="PT_Stitch_Marker", color="#FF8800", mode=db.TYPE_Track)
# Delete Old Tracks
db.deleteMarkers(type=marker_type)
db.deleteMarkers(type=marker_type2)
db.deleteMarkers(type=marker_type3)
db.deleteMarkers(type=marker_type4)
db.deleteTracks(type=marker_type2)
db.deleteTracks(type=marker_type4)
# Start Iteration over Images
print('Starting Iteration')
images = db.getImageIterator(start_frame=20)#start_frame=start_frame, end_frame=3)
# images = db.getImageIterator(start_frame=10272, end_frame=10311)#start_frame=start_frame, end_frame=3)
start = time()
for image in images:
print(time()-start)
start = time()
i = image.get_id()
if db.getMarkerType(name="PT_Prediction_Marker"):
PT_Prediction_Type = db.getMarkerType(name= "PT_Prediction_Marker")
else:
PT_Prediction_Type = db.setMarkerType(name="PT_Prediction_Marker", color="#0000FF")
if db.getMarkerType(name="PT_Stitch_Marker"):
PT_Stitch_Type = db.getMarkerType(name="PT_Stitch_Marker")
else:
PT_Stitch_Type = db.setMarkerType(name="PT_Stitch_Marker", color="#FF8800", mode=db.TYPE_Track)
# Delete Old Tracks
db.deleteMarkers(type=PT_Detection_Type)
db.deleteMarkers(type=PT_Track_Type)
db.deleteMarkers(type=PT_Prediction_Type)
db.deleteMarkers(type=PT_Stitch_Type)
db.deleteTracks(type=PT_Track_Type)
db.deleteTracks(type=PT_Stitch_Type)
# Start Iteration over Images
print('Starting Iteration')
from multiprocessing import Process,Queue,Pipe
# segmentation_queue = Queue(10)
Image_write_queue = Queue()
SegMap_write_queue = Queue()
Detection_write_queue = Queue()
Track_write_queue = Queue()
segmentation_pipe_in, segmentation_pipe_out = Pipe()
detection_pipe_in, detection_pipe_out = Pipe()
marker_type3 = db.setMarkerType(name="PT_Prediction_Marker",
color="#0000FF")
if db.getMarkerType(name="PT_Stitch_Marker"):
marker_type4 = db.getMarkerType(name="PT_Stitch_Marker")
else:
marker_type4 = db.setMarkerType(name="PT_Stitch_Marker",
color="#FF8800",
mode=db.TYPE_Track)
# Delete Old Tracks
db.deleteMarkers(type=marker_type)
db.deleteMarkers(type=marker_type2)
db.deleteMarkers(type=marker_type3)
db.deleteMarkers(type=marker_type4)
db.deleteTracks(type=marker_type2)
db.deleteTracks(type=marker_type4)
# Start Iteration over Images
print('Starting Iteration')
images = db.getImageIterator(
start_frame=10) #start_frame=start_frame, end_frame=3)
for image in images:
start = time()
i = image.get_id()
# Prediction step
MultiKal.predict(u=np.zeros((model.Control_dim, )).T, i=i)
# Segmentation step