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Copula-based conformal bounding box prediction
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Robust events detection
Copula-based conformal bounding box prediction
Commits
14dc7c75
Commit
14dc7c75
authored
10 months ago
by
Bruce Cyusa Mukama
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Drafting optimized metrics
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09988da5
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README.md
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-0
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README.md
demo.ipynb
+237
-337
237 additions, 337 deletions
demo.ipynb
experiments.py
+6
-6
6 additions, 6 deletions
experiments.py
with
245 additions
and
343 deletions
README.md
+
2
−
0
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@@ -2,6 +2,8 @@
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@@ -2,6 +2,8 @@
## Examples
## Examples
-
[
**TBD**
] Animated gif of "Empirical DE-CCP" on a drive scene?
-
[
**TBD**
] Animated gif of "Empirical DE-CCP" on a drive scene?
🚩 Checkout demo.ipynb for more details about the results ⚠️
## Requirements
## Requirements
-
Conda v23.11.0
-
Conda v23.11.0
-
CUDA v12.0+ (drv N° 525.147.05+)
-
CUDA v12.0+ (drv N° 525.147.05+)
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demo.ipynb
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experiments.py
+
6
−
6
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14dc7c75
...
@@ -16,7 +16,7 @@ from src.conformalizers import (
...
@@ -16,7 +16,7 @@ from src.conformalizers import (
)
)
VERSION
=
"
__release
"
VERSION
=
"
__
_
release
"
EPSILONS
=
np
.
array
([
0.01
,
0.05
,
0.1
,
0.2
])
#, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9])
EPSILONS
=
np
.
array
([
0.01
,
0.05
,
0.1
,
0.2
])
#, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9])
...
@@ -30,12 +30,12 @@ def setup_experiment(epsilons: np.ndarray = EPSILONS) -> Tuple:
...
@@ -30,12 +30,12 @@ def setup_experiment(epsilons: np.ndarray = EPSILONS) -> Tuple:
]
]
parameters
=
[
parameters
=
[
{
'
epsilon
'
:
eps
,
{
'
epsilon
'
:
eps
,
'
k_folds
'
:
3
,
#
10,
'
k_folds
'
:
10
,
'
cal_ratio
'
:
0.15
,
#0.15,
'
cal_ratio
'
:
0.15
,
'
val_size
'
:
100
,
'
val_size
'
:
100
,
'
iou_threshold
'
:
0.3
,
'
iou_threshold
'
:
0.3
,
'
confidence_threshold
'
:
0.3
,
'
confidence_threshold
'
:
0.3
,
'
epochs
'
:
2
,
#
100,
'
epochs
'
:
100
,
'
from_scratch
'
:
False
,
'
from_scratch
'
:
False
,
'
device
'
:
torch
.
device
(
'
cuda:0
'
)
'
device
'
:
torch
.
device
(
'
cuda:0
'
)
}
for
eps
in
epsilons
}
for
eps
in
epsilons
...
@@ -74,8 +74,8 @@ if __name__ == "__main__":
...
@@ -74,8 +74,8 @@ if __name__ == "__main__":
warnings
.
simplefilter
(
"
ignore
"
)
warnings
.
simplefilter
(
"
ignore
"
)
detectors
=
[
detectors
=
[
CorrelatedDetector
(),
CorrelatedDetector
(),
#
CorrelatedDetector(cov_matrix=None),
CorrelatedDetector
(
cov_matrix
=
None
),
#
YOLOv8()
YOLOv8
()
]
]
res
=
UQEvalResults
()
res
=
UQEvalResults
()
label
=
f
'
UQ_experiments
{
VERSION
}
'
label
=
f
'
UQ_experiments
{
VERSION
}
'
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