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ultralytics 8.0.181 RTDETR, MLFlow fixes and Examples updates (#4927)

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Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: Jordane Sikati <jordanesikati@pusan.ac.kr>
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Co-authored-by: Akash A Desai <62583018+akashAD98@users.noreply.github.com>
Co-authored-by: Lukas Hennies <45569834+Gornoka@users.noreply.github.com>
Co-authored-by: 唐洁 <tangjie1953479@tongji.edu.cn>
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Glenn Jocher 2023-09-18 14:12:34 +02:00 • committed by GitHub
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commit 742ec7fb1d
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9 changed files with 46 additions and 26 deletions
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2
ultralytics/__init__.py
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@ -1,6 +1,6 @@
# Ultralytics YOLO 🚀, AGPL-3.0 license
__version__ = '8.0.180'
__version__ = '8.0.181'
from ultralytics.models import RTDETR, SAM, YOLO
from ultralytics.models.fastsam import FastSAM

3
ultralytics/models/utils/ops.py
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@ -103,6 +103,9 @@ class HungarianMatcher(nn.Module):
if self.with_mask:
C += self._cost_mask(bs, gt_groups, masks, gt_mask)
# Set invalid values (NaNs and infinities) to 0 (fixes ValueError: matrix contains invalid numeric entries)
C[C.isnan() | C.isinf()] = 0.0
C = C.view(bs, nq, -1).cpu()
indices = [linear_sum_assignment(c[i]) for i, c in enumerate(C.split(gt_groups, -1))]
gt_groups = torch.as_tensor([0, *gt_groups[:-1]]).cumsum_(0)

19
ultralytics/utils/callbacks/mlflow.py
View file

@ -1,6 +1,6 @@
# Ultralytics YOLO 🚀, AGPL-3.0 license
from ultralytics.utils import LOGGER, ROOT, SETTINGS, TESTS_RUNNING, colorstr
from ultralytics.utils import LOGGER, SETTINGS, TESTS_RUNNING, colorstr
try:
assert not TESTS_RUNNING # do not log pytest
@ -8,7 +8,7 @@ try:
import mlflow
assert hasattr(mlflow, '__version__') # verify package is not directory
PREFIX = colorstr('MLFlow:')
import os
import re
@ -25,15 +25,13 @@ def on_pretrain_routine_end(trainer):
if mlflow:
mlflow_location = os.environ['MLFLOW_TRACKING_URI'] # "http://192.168.xxx.xxx:5000"
LOGGER.debug(f'{PREFIX} tracking uri: {mlflow_location}')
mlflow.set_tracking_uri(mlflow_location)
experiment_name = os.environ.get('MLFLOW_EXPERIMENT_NAME') or trainer.args.project or '/Shared/YOLOv8'
run_name = os.environ.get('MLFLOW_RUN') or trainer.args.name
experiment = mlflow.get_experiment_by_name(experiment_name)
if experiment is None:
mlflow.create_experiment(experiment_name)
mlflow.set_experiment(experiment_name)
experiment = mlflow.set_experiment(experiment_name) # change since mlflow does this now by default
mlflow.autolog()
prefix = colorstr('MLFlow: ')
try:
run, active_run = mlflow, mlflow.active_run()
@ -58,10 +56,9 @@ def on_train_end(trainer):
if mlflow:
run.log_artifact(trainer.last)
run.log_artifact(trainer.best)
run.pyfunc.log_model(artifact_path=experiment_name,
code_path=[str(ROOT.parent)],
artifacts={'model_path': str(trainer.save_dir)},
python_model=run.pyfunc.PythonModel())
run.log_artifact(trainer.save_dir)
mlflow.end_run()
LOGGER.debug(f'{PREFIX} ending run')
callbacks = {