How to config tlt-train to save the best performed model

[Morganh]

If you want to check every epochs’ mAP, set as below.

evaluation_config {
validation_period_during_training: 1
first_validation_epoch: 1

Then you will find all the mAP result for each tlt model.
All the tlt model is saved in experiment_dir_unpruned/

For how to check which tlt model belongs to nth epoch, refer to

Detectnet_v2 checkpoint interval unexpected results

I hope this script will help others import os, glob trained_model = glob.glob("trained_model/model*.tlt") trained_model = sorted(trained_model, key=lambda x: int(x.rsplit("-")[1].rstrip(".tlt"))) for epoch, checkpoint in enumerate(trained_model): # checkpoint = os.path.basename(checkpoint) print("epoch: {}, checkpoint: {}".format(epoch, checkpoint)) Output epoch: 0, checkpoint: trained_model/model.step-0.tlt epoch: 1, checkpoint: trained_model/model.step-403.tlt epoch: 2, checkpoint…