def _evaluate(Gt, Hy, threshold, cost_fun, info=False, debug_info=False):
if debug_info:
fp, m, mme, c, d, g, FN_pairs, FP_pairs, MME_pairs = MOTM.evaluate(
Gt, Hy, threshold, cost_fun, debug_info=True)
else:
fp, m, mme, c, d, g = MOTM.evaluate(Gt, Hy, threshold, cost_fun)
FN = np.sum(m)
FP = np.sum(fp)
IDSW = np.sum(mme)
GT = np.sum(g)
mota = 1 - (FN + FP + IDSW) / GT
result = [mota]
if info:
result.append({'FN': FN, 'FP': FP, 'IDSW': IDSW, 'GT': GT})
if debug_info:
result.append({"FN": FN_pairs, "FP": FP_pairs, "IDSW": MME_pairs})
if len(result) > 1:
return result
else:
return result[0]
def test_motm_1mme(self):
Gt = np.array([
[1, 1, 0, 0],
[2, 1, 0, 0]
])
Hy = np.array([
[1, 1, 0, 0],
[2, 2, 0, 0]
])
cost = lambda a, b: la.norm(a-b)
fp, m, mme, c, d, g = MOTM.evaluate(Gt, Hy, 10, cost)
self.assertEqual(len(fp), 2)
self.assertEqual(len(m), 2)
self.assertEqual(len(mme), 2)
self.assertEqual(len(c), 2)
self.assertEqual(len(d), 2)
self.assertEqual(len(g), 2)
self.assertEqual(np.sum(fp), 0)
self.assertEqual(np.sum(m), 0)
self.assertEqual(np.sum(mme), 1)
self.assertEqual(np.sum(d), 0)
self.assertEqual(np.sum(g), 2)
self.assertEqual(np.sum(c), 2)
def test_motm_fp_with_debug_info(self):
Gt = np.array([
[1, 1, 0, 0],
[1, 2, 10, 10],
[2, 1, 0, 0]
])
Hy = np.array([
[1, 2, 10, 10],
[1, 3, 20, 20],
[1, 4, 30, 30],
[2, 1, 0, 0],
[1, 1, 0, 0],
[2, 5, 88, 99]
])
cost = lambda a, b: la.norm(a-b)
fp, m, mme, c, d, g, FN_pairs, FP_pairs, MME_pairs =\
MOTM.evaluate(Gt, Hy, 5, cost,
debug_info=True)
self.assertEqual(len(FN_pairs), 0)
self.assertEqual(len(FP_pairs), 3)
self.assertEqual(len(MME_pairs), 0)
self.assertEqual(FP_pairs[0][0], 1)
self.assertEqual(FP_pairs[1][0], 1)
self.assertEqual(FP_pairs[2][0], 2)
self.assertEqual(FP_pairs[0][2], 20)
self.assertEqual(FP_pairs[1][2], 30)
self.assertEqual(FP_pairs[2][2], 88)
self.assertEqual(len(fp), 2)
self.assertEqual(len(m), 2)
self.assertEqual(len(mme), 2)
self.assertEqual(len(c), 2)
self.assertEqual(len(d), 2)
self.assertEqual(len(g), 2)
self.assertEqual(np.sum(fp), 3)
self.assertEqual(np.sum(m), 0)
self.assertEqual(np.sum(mme), 0)
self.assertEqual(np.sum(d), 0)
self.assertEqual(np.sum(g), 3)
self.assertEqual(np.sum(c), 3)
def evaluate(Gt, Hy, threshold):
""" Ground-truth vs hypothesis for the
Multiple Object Tracking Precision
Gt: [
(frame, pid, x, y)
]
Hy: [
(frame, pid, x, y)
]
threshold: after which no correspondence is possible
"""
cost_fun = lambda a, b: la.norm(a-b)
fp, m, mme, c, d, g = MOTM.evaluate(Gt, Hy, threshold, cost_fun)
D = np.sum(d)
C = np.sum(c)
return D/C
def test_motm_interrupt(self):
Gt = np.array([
[1, 1, 0, 0],
[2, 1, 0, 0],
[5, 1, 0, 0],
[6, 1, 0, 0],
[7, 1, 0, 0],
[8, 1, 0, 0]
])
Hy = np.array([
[1, 1, 0, 0],
[2, 1, 0, 0],
[5, 1, 0, 0],
[6, 1, 0, 0],
[7, 1, 0, 0],
[8, 1, 0, 0]
])
cost = lambda a, b: la.norm(a-b)
fp, m, mme, c, d, g = MOTM.evaluate(Gt, Hy, 10, cost)
self.assertEqual(len(fp), 8)
self.assertEqual(len(m), 8)
self.assertEqual(len(mme), 8)
self.assertEqual(len(c), 8)
self.assertEqual(len(d), 8)
self.assertEqual(len(g), 8)
self.assertEqual(np.sum(fp), 0)
self.assertEqual(np.sum(m), 0)
self.assertEqual(np.sum(mme), 0)
self.assertEqual(np.sum(d), 0)
self.assertEqual(np.sum(g), 6)
self.assertEqual(np.sum(c), 6)
