Comet Logging and Visualization Integration (#9232)

* add comet to logger interface

* add comet logger

* add support for updated parameters

* clean up offline logger creation

* update callback args for comet logger

* add comet optimizer

* add optimizer config

* add comet README

* update tutorial notebook with Comet section

* add option to log class level metrics

* add support for class level metrics and confusion matrix

* handle errors when adding files to artifacts

* fix typo

* clean resume workflow

* updates for HPO

* update comet README

* fix typo in comet README

* update code snippets in comet README

* update comet links in tutorial

* updated links

* change optimizer batch size param and update comet README image

* update comet section in tutorial

* use prexisting cmd line flags to configure logger

* update artifact upload/download flow

* remove come remove comet logger specific cmd line args

* move downloading weights into comet logger code

* remove extra argparse

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* change checkpoint logging flow to follow offline logger

* update resume flow

* add comet logger to remote dataset property

* update cmd line args in hpo

* set types for integer/float env variables

* update README

* fix typo in README

* default to always logging model predictions

* Update tutorial.ipynb

* Update train.py

* Add Comet to Integrations table

* Update README.md

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

Co-authored-by: Ayush Chaurasia <ayush.chaurarsia@gmail.com>
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

train.py

@@ -52,6 +52,7 @@ from utils.general import (LOGGER, check_amp, check_dataset, check_file, check_g
                            init_seeds, intersect_dicts, labels_to_class_weights, labels_to_image_weights, methods,
                            one_cycle, print_args, print_mutation, strip_optimizer, yaml_save)
 from utils.loggers import Loggers
+from utils.loggers.comet.comet_utils import check_comet_resume
 from utils.loggers.wandb.wandb_utils import check_wandb_resume
 from utils.loss import ComputeLoss
 from utils.metrics import fitness
@@ -330,7 +331,7 @@ def train(hyp, opt, device, callbacks):  # hyp is path/to/hyp.yaml or hyp dictio
                 mem = f'{torch.cuda.memory_reserved() / 1E9 if torch.cuda.is_available() else 0:.3g}G'  # (GB)
                 pbar.set_description(('%11s' * 2 + '%11.4g' * 5) %
                                      (f'{epoch}/{epochs - 1}', mem, *mloss, targets.shape[0], imgs.shape[-1]))
-                callbacks.run('on_train_batch_end', model, ni, imgs, targets, paths)
+                callbacks.run('on_train_batch_end', model, ni, imgs, targets, paths, list(mloss))
                 if callbacks.stop_training:
                     return
             # end batch ------------------------------------------------------------------------------------------------
@@ -465,11 +466,11 @@ def parse_opt(known=False):
     parser.add_argument('--seed', type=int, default=0, help='Global training seed')
     parser.add_argument('--local_rank', type=int, default=-1, help='Automatic DDP Multi-GPU argument, do not modify')
 
-    # 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')
+    # Logger arguments
+    parser.add_argument('--entity', default=None, help='Entity')
+    parser.add_argument('--upload_dataset', nargs='?', const=True, default=False, help='Upload data, "val" option')
+    parser.add_argument('--bbox_interval', type=int, default=-1, help='Set bounding-box image logging interval')
+    parser.add_argument('--artifact_alias', type=str, default='latest', help='Version of dataset artifact to use')
 
     return parser.parse_known_args()[0] if known else parser.parse_args()
 
@@ -481,8 +482,8 @@ def main(opt, callbacks=Callbacks()):
         check_git_status()
         check_requirements()
 
-    # Resume
-    if opt.resume and not (check_wandb_resume(opt) or opt.evolve):  # resume from specified or most recent last.pt
+    # Resume (from specified or most recent last.pt)
+    if opt.resume and not check_wandb_resume(opt) and not check_comet_resume(opt) or opt.evolve:
         last = Path(check_file(opt.resume) if isinstance(opt.resume, str) else get_latest_run())
         opt_yaml = last.parent.parent / 'opt.yaml'  # train options yaml
         opt_data = opt.data  # original dataset