Skip to content

ValueError: Misconfigured conditions in the pytorch_config: None. #2970

Description

@HLH2000

Is there an existing issue for this?

  • I have searched the existing issues

Operating System

Windows 11

DeepLabCut version

3.0.0rc8

What engine are you using?

pytorch

DeepLabCut mode

multi animal

Device type

NVIDIA Geforce RTX3080

Bug description 🐛

"When I tried to evaluate my training results, I encountered a failed code.
(P.S.: Net type: ctd_prenet_rtmpose_m)"

Steps To Reproduce

No response

Relevant log output

Traceback (most recent call last):
  File "C:\Users\HLH\AppData\Local\anaconda3\envs\dlc3\lib\site-packages\deeplabcut\gui\tabs\evaluate_network.py", line 207, in evaluate_network
    deeplabcut.evaluate_network(
  File "C:\Users\HLH\AppData\Local\anaconda3\envs\dlc3\lib\site-packages\deeplabcut\compat.py", line 558, in evaluate_network
    return evaluate_network(
  File "C:\Users\HLH\AppData\Local\anaconda3\envs\dlc3\lib\site-packages\deeplabcut\pose_estimation_pytorch\apis\evaluation.py", line 832, in evaluate_network
    evaluate_snapshot(
  File "C:\Users\HLH\AppData\Local\anaconda3\envs\dlc3\lib\site-packages\deeplabcut\pose_estimation_pytorch\apis\evaluation.py", line 579, in evaluate_snapshot
    results, predictions_for_split = evaluate(
  File "C:\Users\HLH\AppData\Local\anaconda3\envs\dlc3\lib\site-packages\deeplabcut\pose_estimation_pytorch\apis\evaluation.py", line 143, in evaluate
    predictions = predict(pose_runner, loader, mode, detector_runner=detector_runner)
  File "C:\Users\HLH\AppData\Local\anaconda3\envs\dlc3\lib\site-packages\deeplabcut\pose_estimation_pytorch\apis\evaluation.py", line 90, in predict
    conditions = ctd.load_conditions_for_evaluation(loader, image_paths)
  File "C:\Users\HLH\AppData\Local\anaconda3\envs\dlc3\lib\site-packages\deeplabcut\pose_estimation_pytorch\apis\ctd.py", line 126, in load_conditions_for_evaluation
    raise ValueError(error_message)
ValueError: Misconfigured conditions in the pytorch_config: None. Valid examples:

Example: Using a bottom-up model for conditions
  
  data:
    conditions:
      config_path: /path/to/model-dir/pytorch_config.yaml
      snapshot_path: /path/to/model-dir/snapshot-best-150.pth
  
Example: Loading the predictions for snapshot-250.pt of shuffle 1.
  
  data:
    conditions:
      shuffle: 1
      snapshot: snapshot-250.pt
  
Example: Loading the predictions for the snapshot with index 2 of shuffle 1.
  
  data:
    conditions:
      shuffle: 1
      snapshot_index: 2
  

Example: Loading the predictions contained in an h5 file.
  
  data:
    conditions: /path/to/bu_predictions.h5
  
Example: Loading the predictions contained in an json file.
  
  data:
    conditions: /path/to/bu_predictions.json

Anything else?

config.txt

pip list.txt

Code of Conduct

Metadata

Metadata

Assignees

Labels

CTDContidional Top-DownDLC3.0🔥howtousedlcissue regarding the use of DeepLabCut

Type

No type

Projects

No projects

Milestone

No milestone

Relationships

None yet

Development

No branches or pull requests

Issue actions