Examples: query, "exact match", wildcard*, wild?ard, wild*rd
Fuzzy search: cake~ (finds cakes, bake)
Term boost: "red velvet"^4, chocolate^2
Field grouping: tags:(+work -"fun-stuff")
Escaping: Escape characters +-&|!(){}[]^"~*?:\ with \, e.g. \+
Range search: properties.timestamp:[1587729413488 TO *] (inclusive), properties.title:{A TO Z}(excluding A and Z)
Combinations: chocolate AND vanilla, chocolate OR vanilla, (chocolate OR vanilla) NOT "vanilla pudding"
Field search: properties.title:"The Title" AND text
Profile picture
CleanOwl48
Moderator
2 Questions, 3 Answers
  Active since 27 September 2024
  Last activity 19 days ago

Reputation

0

Badges 1

3 × Eureka!
0 Votes
2 Answers
37 Views
0 Votes 2 Answers 37 Views
Hi Again 👏 I am using ultralytics to train yolov8 . ClearML automatically track the experiment for me. I try to add upload the best and last checkpoint maun...
20 days ago
0 Votes
3 Answers
63 Views
0 Votes 3 Answers 63 Views
Hi folks! I am trying to create a pipeline with ClearML and Ultralytics. While there's already amazing integration among the tools, I found some difficulties...
26 days ago
0 Hi Folks! I Am Trying To Create A Pipeline With Clearml And Ultralytics. While There'S Already Amazing Integration Among The Tools, I Found Some Difficulties Trying To Utilized All The Magic Features From Clearml. Specifically:

I deepdive into Ultralytics code and found that clearML is not logging the expereiment, but rather the model used in checking amp on the machine, specifically def check_amp(model): create a new model and get tracked, which is not the one for training.
Thanks! I will test it for a bit and see if I can utilized the model feature in clearml

26 days ago
0 Hi Folks! I Am Trying To Create A Pipeline With Clearml And Ultralytics. While There'S Already Amazing Integration Among The Tools, I Found Some Difficulties Trying To Utilized All The Magic Features From Clearml. Specifically:

hmmm it seems that it is not the case. Neverthless, the following code works:

input_model: InputModel = InputModel.import_model(name="test_input", weights_url="model/yolov8n.pt")
task.connect(input_model)

model = YOLO(input_model.get_local_copy())
25 days ago
0 Hi Again

just fyi i read Model SDK doc for several time and didn't expect the option is inside Task . Many Thanks!

20 days ago