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ultralytics 8.0.41 TF SavedModel and EdgeTPU export (#1034)

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Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Noobtoss <96134731+Noobtoss@users.noreply.github.com>
Co-authored-by: Ayush Chaurasia <ayush.chaurarsia@gmail.com>
This commit is contained in:
Glenn Jocher
2023-02-20 01:27:28 +01:00
committed by GitHub
parent 4b866c9718
commit f6e393c1d2
64 changed files with 604 additions and 351 deletions
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32
ultralytics/yolo/utils/callbacks/clearml.py
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@ -1,5 +1,5 @@
# 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:
@ -7,6 +7,7 @@ try:
from clearml import Task
assert clearml.__version__ # verify package is not directory
assert not TESTS_RUNNING # do not log pytest
except (ImportError, AssertionError):
clearml = None
@ -19,14 +20,16 @@ def _log_images(imgs_dict, group='', step=0):
def on_pretrain_routine_start(trainer):
# TODO: reuse existing task
task = Task.init(project_name=trainer.args.project or 'YOLOv8',
task_name=trainer.args.name,
tags=['YOLOv8'],
output_uri=True,
reuse_last_task_id=False,
auto_connect_frameworks={'pytorch': False})
task.connect(vars(trainer.args), name='General')
try:
task = Task.init(project_name=trainer.args.project or 'YOLOv8',
task_name=trainer.args.name,
tags=['YOLOv8'],
output_uri=True,
reuse_last_task_id=False,
auto_connect_frameworks={'pytorch': False})
task.connect(vars(trainer.args), name='General')
except Exception as e:
LOGGER.warning(f'WARNING ⚠️ ClearML not initialized correctly, not logging this run. {e}')
def on_train_epoch_end(trainer):
@ -35,18 +38,19 @@ def on_train_epoch_end(trainer):
def on_fit_epoch_end(trainer):
if trainer.epoch == 0:
task = Task.current_task()
if task and trainer.epoch == 0:
model_info = {
'Parameters': get_num_params(trainer.model),
'GFLOPs': round(get_flops(trainer.model), 3),
'Inference speed (ms/img)': round(trainer.validator.speed[1], 3)}
Task.current_task().connect(model_info, name='Model')
task.connect(model_info, name='Model')
def on_train_end(trainer):
Task.current_task().update_output_model(model_path=str(trainer.best),
model_name=trainer.args.name,
auto_delete_file=False)
task = Task.current_task()
if task:
task.update_output_model(model_path=str(trainer.best), model_name=trainer.args.name, auto_delete_file=False)
callbacks = {