Evaluate script: review of command-line arguments

[sfmig]

This PR changes the CLI arguments of the evaluate script to better match the training script.

The most common use would be to run:

evaluate-detector ---trained_model_path <path-to-ckpt>

This will load the trained model and use its config to run the evaluation. Note that it is important that we use the config used in training, to make the same dataset and use the correct test split.

However, if a dataset or config file is specified via CLI, the parameters will be overwritten.

Other additions

• organises config .yaml parameters into sections (feel free to give feedback, not sure what is most intuitive).
• adds evaluate logs to MLFlow,
• adds a small fix to save frames from test set,
• adds an option to save frames in a selected output directory (if none, uses a timestamped directory),
• fixes test for saving frames and adapt to check timestamped directory.

I will do the tests in a separate PR 😬 ---> #199

[codecov-commenter]

Codecov Report

Attention: Patch coverage is 41.80328% with 71 lines in your changes missing coverage. Please review.

Project coverage is 37.11%. Comparing base (5a47ee0) to head (8bb9d9c).

Files	Patch %	Lines
crabs/detection_tracking/evaluate_utils.py	51.16%	42 Missing ⚠️
crabs/detection_tracking/evaluate_model.py	0.00%	28 Missing ⚠️
crabs/detection_tracking/visualization.py	85.71%	1 Missing ⚠️

Additional details and impacted files

@@            Coverage Diff             @@
##             main     #172      +/-   ##
==========================================
- Coverage   37.73%   37.11%   -0.63%     
==========================================
  Files          20       20              
  Lines        1349     1412      +63     
==========================================
+ Hits          509      524      +15     
- Misses        840      888      +48     

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[nikk-nikaznan]

Looking good to me. Just wonder if we should move some of the functions like the get_.. to evaluate_utils to make the evaluate_model a bit cleaner.