Clearml integration cleanup

README.md

@@ -203,7 +203,7 @@ Get started in seconds with our verified environments. Click each icon below for
 
 |Weights and Biases|Roboflow|ClearML ⭐ NEW|
 |:-:|:-:|:-:|
-|Automatically track and visualize all your YOLOv5 training runs in the cloud with [Weights & Biases](https://wandb.ai/site?utm_campaign=repo_yolo_readme)|Label and export your custom datasets directly to YOLOv5 for training with [Roboflow](https://roboflow.com/?ref=ultralytics) |Track experiments, vizusalise them and remotely train YOLOv5 in the cloud or locally using [ClearML](https://clear.ml/?ref=ultralytics)
+|Automatically track and visualize all your YOLOv5 training runs in the cloud with [Weights & Biases](https://wandb.ai/site?utm_campaign=repo_yolo_readme)|Label and export your custom datasets directly to YOLOv5 for training with [Roboflow](https://roboflow.com/?ref=ultralytics) |Track experiments, vizusalise them and **remotely train YOLOv5** in the cloud or locally using [ClearML](https://clear.ml/?ref=ultralytics)
 
 <!-- ## <div align="center">Compete and Win</div>
 

utils/general.py

@@ -436,7 +436,7 @@ def check_file(file, suffix=''):
             torch.hub.download_url_to_file(url, file)
             assert Path(file).exists() and Path(file).stat().st_size > 0, f'File download failed: {url}'  # check
         return file
-    elif file.startswith('clearml:'):
+    elif file.startswith('clearml://'):
         # ClearML Dataset ID
         return file
     else:  # search

utils/loggers/clearml/clearml_utils.py

@@ -17,7 +17,7 @@
 
 
 def construct_dataset(clearml_info_string):
-    dataset_id = clearml_info_string.replace('clearml:', '')
+    dataset_id = clearml_info_string.replace('clearml://', '')
     dataset = Dataset.get(dataset_id=dataset_id)
     dataset_root_path = Path(dataset.get_local_copy())
 
@@ -82,14 +82,15 @@ def __init__(self, opt, hyp):
                 tags=['YOLOv5'],
                 output_uri=True,
                 auto_connect_frameworks={'pytorch': False}
+                # We disconnect pytorch auto-detection, because we added manual model save points in the code
             )
             # ClearML's hooks will already grab all general parameters
             # Only the hyperparameters coming from the yaml config file
             # will have to be added manually!
             self.task.connect(hyp, name='Hyperparameters')
 
             # Get ClearML Dataset Version if requested
-            if opt.data.startswith('clearml:'):
+            if opt.data.startswith('clearml://'):
                 # data_dict should have the following keys:
                 # names, nc (number of classes), test, train, val (all three relative paths to ../datasets)
                 self.data_dict = construct_dataset(opt.data)