diff --git a/yolov5/models/utils/loggers/comet/comet_utils.py b/yolov5/models/utils/loggers/comet/comet_utils.py
new file mode 100644
index 0000000000000000000000000000000000000000..27600761ad2843a6ab66aa22ad06782bb4b7eea7
--- /dev/null
+++ b/yolov5/models/utils/loggers/comet/comet_utils.py
@@ -0,0 +1,150 @@
+import logging
+import os
+from urllib.parse import urlparse
+
+try:
+    import comet_ml
+except (ModuleNotFoundError, ImportError):
+    comet_ml = None
+
+import yaml
+
+logger = logging.getLogger(__name__)
+
+COMET_PREFIX = 'comet://'
+COMET_MODEL_NAME = os.getenv('COMET_MODEL_NAME', 'yolov5')
+COMET_DEFAULT_CHECKPOINT_FILENAME = os.getenv('COMET_DEFAULT_CHECKPOINT_FILENAME', 'last.pt')
+
+
+def download_model_checkpoint(opt, experiment):
+    model_dir = f'{opt.project}/{experiment.name}'
+    os.makedirs(model_dir, exist_ok=True)
+
+    model_name = COMET_MODEL_NAME
+    model_asset_list = experiment.get_model_asset_list(model_name)
+
+    if len(model_asset_list) == 0:
+        logger.error(f'COMET ERROR: No checkpoints found for model name : {model_name}')
+        return
+
+    model_asset_list = sorted(
+        model_asset_list,
+        key=lambda x: x['step'],
+        reverse=True,
+    )
+    logged_checkpoint_map = {asset['fileName']: asset['assetId'] for asset in model_asset_list}
+
+    resource_url = urlparse(opt.weights)
+    checkpoint_filename = resource_url.query
+
+    if checkpoint_filename:
+        asset_id = logged_checkpoint_map.get(checkpoint_filename)
+    else:
+        asset_id = logged_checkpoint_map.get(COMET_DEFAULT_CHECKPOINT_FILENAME)
+        checkpoint_filename = COMET_DEFAULT_CHECKPOINT_FILENAME
+
+    if asset_id is None:
+        logger.error(f'COMET ERROR: Checkpoint {checkpoint_filename} not found in the given Experiment')
+        return
+
+    try:
+        logger.info(f'COMET INFO: Downloading checkpoint {checkpoint_filename}')
+        asset_filename = checkpoint_filename
+
+        model_binary = experiment.get_asset(asset_id, return_type='binary', stream=False)
+        model_download_path = f'{model_dir}/{asset_filename}'
+        with open(model_download_path, 'wb') as f:
+            f.write(model_binary)
+
+        opt.weights = model_download_path
+
+    except Exception as e:
+        logger.warning('COMET WARNING: Unable to download checkpoint from Comet')
+        logger.exception(e)
+
+
+def set_opt_parameters(opt, experiment):
+    """Update the opts Namespace with parameters
+    from Comet's ExistingExperiment when resuming a run
+
+    Args:
+        opt (argparse.Namespace): Namespace of command line options
+        experiment (comet_ml.APIExperiment): Comet API Experiment object
+    """
+    asset_list = experiment.get_asset_list()
+    resume_string = opt.resume
+
+    for asset in asset_list:
+        if asset['fileName'] == 'opt.yaml':
+            asset_id = asset['assetId']
+            asset_binary = experiment.get_asset(asset_id, return_type='binary', stream=False)
+            opt_dict = yaml.safe_load(asset_binary)
+            for key, value in opt_dict.items():
+                setattr(opt, key, value)
+            opt.resume = resume_string
+
+    # Save hyperparameters to YAML file
+    # Necessary to pass checks in training script
+    save_dir = f'{opt.project}/{experiment.name}'
+    os.makedirs(save_dir, exist_ok=True)
+
+    hyp_yaml_path = f'{save_dir}/hyp.yaml'
+    with open(hyp_yaml_path, 'w') as f:
+        yaml.dump(opt.hyp, f)
+    opt.hyp = hyp_yaml_path
+
+
+def check_comet_weights(opt):
+    """Downloads model weights from Comet and updates the
+    weights path to point to saved weights location
+
+    Args:
+        opt (argparse.Namespace): Command Line arguments passed
+            to YOLOv5 training script
+
+    Returns:
+        None/bool: Return True if weights are successfully downloaded
+            else return None
+    """
+    if comet_ml is None:
+        return
+
+    if isinstance(opt.weights, str):
+        if opt.weights.startswith(COMET_PREFIX):
+            api = comet_ml.API()
+            resource = urlparse(opt.weights)
+            experiment_path = f'{resource.netloc}{resource.path}'
+            experiment = api.get(experiment_path)
+            download_model_checkpoint(opt, experiment)
+            return True
+
+    return None
+
+
+def check_comet_resume(opt):
+    """Restores run parameters to its original state based on the model checkpoint
+    and logged Experiment parameters.
+
+    Args:
+        opt (argparse.Namespace): Command Line arguments passed
+            to YOLOv5 training script
+
+    Returns:
+        None/bool: Return True if the run is restored successfully
+            else return None
+    """
+    if comet_ml is None:
+        return
+
+    if isinstance(opt.resume, str):
+        if opt.resume.startswith(COMET_PREFIX):
+            api = comet_ml.API()
+            resource = urlparse(opt.resume)
+            experiment_path = f'{resource.netloc}{resource.path}'
+            experiment = api.get(experiment_path)
+            set_opt_parameters(opt, experiment)
+            download_model_checkpoint(opt, experiment)
+
+            return True
+
+    return None