Add git info to cls, seg checkpoints

classify/train.py

@@ -40,7 +40,7 @@
 from models.experimental import attempt_load
 from models.yolo import ClassificationModel, DetectionModel
 from utils.dataloaders import create_classification_dataloader
-from utils.general import (DATASETS_DIR, LOGGER, TQDM_BAR_FORMAT, WorkingDirectory, check_git_status,
+from utils.general import (DATASETS_DIR, GIT, LOGGER, TQDM_BAR_FORMAT, WorkingDirectory, check_git_status,
                            check_requirements, colorstr, download, increment_path, init_seeds, print_args, yaml_save)
 from utils.loggers import GenericLogger
 from utils.plots import imshow_cls
@@ -237,6 +237,7 @@ def train(opt, device):
                     'updates': ema.updates,
                     'optimizer': None,  # optimizer.state_dict(),
                     'opt': vars(opt),
+                    'git': GIT,  # {remote, branch, commit} if a git repo
                     'date': datetime.now().isoformat()}
 
                 # Save last, best and delete

segment/train.py

@@ -46,7 +46,7 @@
 from utils.autobatch import check_train_batch_size
 from utils.callbacks import Callbacks
 from utils.downloads import attempt_download, is_url
-from utils.general import (LOGGER, TQDM_BAR_FORMAT, check_amp, check_dataset, check_file, check_git_status,
+from utils.general import (GIT, LOGGER, TQDM_BAR_FORMAT, check_amp, check_dataset, check_file, check_git_status,
                            check_img_size, check_requirements, check_suffix, check_yaml, colorstr, get_latest_run,
                            increment_path, init_seeds, intersect_dicts, labels_to_class_weights,
                            labels_to_image_weights, one_cycle, print_args, print_mutation, strip_optimizer, yaml_save)
@@ -390,6 +390,7 @@ def train(hyp, opt, device, callbacks):  # hyp is path/to/hyp.yaml or hyp dictio
                     'updates': ema.updates,
                     'optimizer': optimizer.state_dict(),
                     'opt': vars(opt),
+                    'git': GIT,  # {remote, branch, commit} if a git repo
                     'date': datetime.now().isoformat()}
 
                 # Save last, best and delete
@@ -498,12 +499,6 @@ def parse_opt(known=False):
     parser.add_argument('--mask-ratio', type=int, default=4, help='Downsample the truth masks to saving memory')
     parser.add_argument('--no-overlap', action='store_true', help='Overlap masks train faster at slightly less mAP')
 
-    # Weights & Biases arguments
-    # parser.add_argument('--entity', default=None, help='W&B: Entity')
-    # parser.add_argument('--upload_dataset', nargs='?', const=True, default=False, help='W&B: Upload data, "val" option')
-    # parser.add_argument('--bbox_interval', type=int, default=-1, help='W&B: Set bounding-box image logging interval')
-    # parser.add_argument('--artifact_alias', type=str, default='latest', help='W&B: Version of dataset artifact to use')
-
     return parser.parse_known_args()[0] if known else parser.parse_args()
 
 

train.py

@@ -376,7 +376,7 @@ def train(hyp, opt, device, callbacks):  # hyp is path/to/hyp.yaml or hyp dictio
                     'updates': ema.updates,
                     'optimizer': optimizer.state_dict(),
                     'opt': vars(opt),
-                    'git': GIT,
+                    'git': GIT,  # {remote, branch, commit} if a git repo
                     'date': datetime.now().isoformat()}
 
                 # Save last, best and delete