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ultralytics 8.0.41 TF SavedModel and EdgeTPU export (#1034)

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Co-authored-by: Ayush Chaurasia <ayush.chaurarsia@gmail.com>
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Glenn Jocher 2023-02-20 01:27:28 +01:00 • committed by GitHub
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40
ultralytics/yolo/utils/callbacks/comet.py
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@ -1,41 +1,49 @@
# Ultralytics YOLO 🚀, GPL-3.0 license
from ultralytics.yolo.utils import LOGGER, TESTS_RUNNING
from ultralytics.yolo.utils.torch_utils import get_flops, get_num_params
try:
import comet_ml
except ImportError:
assert not TESTS_RUNNING # do not log pytest
assert comet_ml.__version__ # verify package is not directory
except (ImportError, AssertionError):
comet_ml = None
def on_pretrain_routine_start(trainer):
experiment = comet_ml.Experiment(project_name=trainer.args.project or 'YOLOv8')
experiment.log_parameters(vars(trainer.args))
try:
experiment = comet_ml.Experiment(project_name=trainer.args.project or 'YOLOv8')
experiment.log_parameters(vars(trainer.args))
except Exception as e:
LOGGER.warning(f'WARNING ⚠️ Comet not initialized correctly, not logging this run. {e}')
def on_train_epoch_end(trainer):
experiment = comet_ml.get_global_experiment()
experiment.log_metrics(trainer.label_loss_items(trainer.tloss, prefix='train'), step=trainer.epoch + 1)
if trainer.epoch == 1:
for f in trainer.save_dir.glob('train_batch*.jpg'):
experiment.log_image(f, name=f.stem, step=trainer.epoch + 1)
if experiment:
experiment.log_metrics(trainer.label_loss_items(trainer.tloss, prefix='train'), step=trainer.epoch + 1)
if trainer.epoch == 1:
for f in trainer.save_dir.glob('train_batch*.jpg'):
experiment.log_image(f, name=f.stem, step=trainer.epoch + 1)
def on_fit_epoch_end(trainer):
experiment = comet_ml.get_global_experiment()
experiment.log_metrics(trainer.metrics, step=trainer.epoch + 1)
if trainer.epoch == 0:
model_info = {
'model/parameters': get_num_params(trainer.model),
'model/GFLOPs': round(get_flops(trainer.model), 3),
'model/speed(ms)': round(trainer.validator.speed[1], 3)}
experiment.log_metrics(model_info, step=trainer.epoch + 1)
if experiment:
experiment.log_metrics(trainer.metrics, step=trainer.epoch + 1)
if trainer.epoch == 0:
model_info = {
'model/parameters': get_num_params(trainer.model),
'model/GFLOPs': round(get_flops(trainer.model), 3),
'model/speed(ms)': round(trainer.validator.speed[1], 3)}
experiment.log_metrics(model_info, step=trainer.epoch + 1)
def on_train_end(trainer):
experiment = comet_ml.get_global_experiment()
experiment.log_model('YOLOv8', file_or_folder=str(trainer.best), file_name='best.pt', overwrite=True)
if experiment:
experiment.log_model('YOLOv8', file_or_folder=str(trainer.best), file_name='best.pt', overwrite=True)
callbacks = {