iter=10,
thresh=1e-05,
minit='matrix',
missing='warn')
assert (len(trajectories) == len(labels))
for trajLab in zip(trajectories, labels):
trajLab[0].setClusterIdx(trajLab[1])
# Testing the module
if __name__ == "__main__":
list_trajs = [[(0.0, 0.0), (1.0, 1.0), (2.0, 2.0), (3.0, 3.0)],
[(0.5, 0.5), (1.5, 1.5), (2.5, 2.5), (3.5, 3.5)],
[(12.0, -5.0), (10.0, -2.5), (8.0, 0.0), (6.0, 2.5)],
[(14.0, -7.0), (12.0, -4.5), (10.0, -2.0), (8.0, 0.5)]]
trajs = []
for trj in list_trajs:
temp = Trajectory(-1)
for pt in trj:
temp.addPoint(pt)
trajs.append(temp)
#print(trj, temp)
clust = Clustering()
res = clust.clusterAgglomerartive(trajs, 2)
print(res)
for i in range(20):
color = (random.randint(0, 255), random.randint(0, 255),
random.randint(0, 255))
colors.append(color)
file = open('trajectories_filtered.txt', 'r')
trajs = []
for i, line in enumerate(file):
traj = Trajectory(i)
pts = line.split(',')[:-1]
for pt in pts:
xy = pt.split(' ')
x = float(xy[0])
y = float(xy[1])
xy = (x, y)
traj.addPoint(xy)
trajs.append(traj)
print("[INFO] Read in %d trajectories." % len(trajs))
clust = Clustering()
# res = clust.clusterAgglomerartive(trajs, 5)
res = clust.clusterSpectral(trajs)
print("printing image")
for traj in trajs:
for pt in traj.getPoints():
cv2.circle(mask, (int(pt[0]), int(pt[1])), 1,
colors[traj.getClusterIdx() - 1], -1)
count = [0] * res
