Comet Updates (#3186)

Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
single_channel
Dhruv Nair 1 year ago committed by GitHub
parent 0d91d6df6e
commit a0fa99c4db
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GPG Key ID: 4AEE18F83AFDEB23

@ -46,7 +46,7 @@ def _scale_confidence_score(score):
def _should_log_confusion_matrix(): def _should_log_confusion_matrix():
return os.getenv('COMET_EVAL_LOG_CONFUSION_MATRIX', 'true').lower() == 'true' return os.getenv('COMET_EVAL_LOG_CONFUSION_MATRIX', 'false').lower() == 'true'
def _should_log_image_predictions(): def _should_log_image_predictions():
@ -67,11 +67,12 @@ def _create_experiment(args):
return return
try: try:
comet_mode = _get_comet_mode() comet_mode = _get_comet_mode()
experiment = _get_experiment_type(comet_mode, args.project) _project_name = os.getenv('COMET_PROJECT_NAME', args.project)
experiment = _get_experiment_type(comet_mode, _project_name)
experiment.log_parameters(vars(args)) experiment.log_parameters(vars(args))
experiment.log_others({ experiment.log_others({
'eval_batch_logging_interval': _get_eval_batch_logging_interval(), 'eval_batch_logging_interval': _get_eval_batch_logging_interval(),
'log_confusion_matrix': _should_log_confusion_matrix(), 'log_confusion_matrix_on_eval': _should_log_confusion_matrix(),
'log_image_predictions': _should_log_image_predictions(), 'log_image_predictions': _should_log_image_predictions(),
'max_image_predictions': _get_max_image_predictions_to_log(), }) 'max_image_predictions': _get_max_image_predictions_to_log(), })
experiment.log_other('Created from', 'yolov8') experiment.log_other('Created from', 'yolov8')
@ -195,7 +196,7 @@ def _create_prediction_metadata_map(model_predictions):
def _log_confusion_matrix(experiment, trainer, curr_step, curr_epoch): def _log_confusion_matrix(experiment, trainer, curr_step, curr_epoch):
"""Log the confusion matrix to Weights and Biases experiment.""" """Log the confusion matrix to Comet experiment."""
conf_mat = trainer.validator.confusion_matrix.matrix conf_mat = trainer.validator.confusion_matrix.matrix
names = list(trainer.data['names'].values()) + ['background'] names = list(trainer.data['names'].values()) + ['background']
experiment.log_confusion_matrix( experiment.log_confusion_matrix(

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