Laurent/REVA-QCAV
1
0
Fork 0
mirror of https://github.com/Laurent2916/REVA-QCAV.git synced 2024-11-09 23:12:05 +00:00
Code Issues Packages Projects Releases Wiki Activity

chore: remove unused file

Browse source 
Former-commit-id: bf466229627337e31bff835bd7615b764ab982ac [formerly 919ecf8585bd9910ffd9722ff390e16d265dc2fa]
Former-commit-id: 2e4531522077a9191c55b5952f05bd0c4f2346f4
This commit is contained in:
Laurent Fainsin 2022-09-07 10:43:22 +02:00
parent 3bbc132359
commit db90446eb0
1 changed files with 0 additions and 70 deletions
Show stats Download patch file Download diff file Expand all files Collapse all files

70
src/notebooks/test.py
View file

@ -1,70 +0,0 @@
import torch
from torchmetrics.detection.mean_ap import MeanAveragePrecision
preds = [
dict(
boxes=torch.tensor(
[
[880.0560, 41.7845, 966.9839, 131.3355],
[1421.0029, 682.4420, 1512.7570, 765.2380],
[132.0775, 818.5026, 216.0825, 1020.8573],
]
),
scores=torch.tensor(
[0.9989, 0.9936, 0.0932],
),
labels=torch.tensor(
[1, 1, 1],
),
)
]
target = [
dict(
boxes=torch.tensor(
[[879, 39, 1513, 766]],
),
labels=torch.tensor(
[1],
),
)
]
metric = MeanAveragePrecision()
metric.update(preds, target)
from pprint import pprint
pprint(metric.compute())
# --------------------------------------------------------------------------
preds = [
dict(
boxes=torch.tensor(
[
[880.0560, 41.7845, 1500, 700.3355],
]
),
scores=torch.tensor(
[0.9989],
),
labels=torch.tensor(
[1],
),
)
]
target = [
dict(
boxes=torch.tensor(
[[879, 39, 1513, 766]],
),
labels=torch.tensor(
[1],
),
)
]
metric = MeanAveragePrecision()
metric.update(preds, target)
from pprint import pprint
pprint(metric.compute())