Scripts for traning yolo object detection

[kluge7]

• Removed deprecated files (probably should have been a separate pull request 🤷)
• Add slurm job

[Copilot]

Pull Request Overview

This PR adds training scripts and configurations for running YOLO and U-Net models on the Idun cluster, while restructuring the project to support multiple model training workflows.

Key Changes:

• Added new training directories with scripts for YOLO and U-Net models
• Created SLURM job configurations for GPU-based training on the Idun cluster
• Updated CI/CD workflows to reference the new requirements.txt location

Reviewed Changes

Copilot reviewed 11 out of 13 changed files in this pull request and generated 3 comments.

Show a summary per file

File	Description
yolo_roboflow_training/train.py	Training script for YOLO model using Roboflow datasets
yolo_roboflow_training/requirements.txt	Python dependencies for YOLO training
yolo_roboflow_training/Job.slurm	SLURM configuration for YOLO training jobs
unet_roboflow_training/train.py	Training script for U-Net segmentation model
unet_roboflow_training/test.py	Inference script for testing trained U-Net models
unet_roboflow_training/requirements.txt	Python dependencies for U-Net training
unet_roboflow_training/Job.slurm	SLURM configuration for U-Net training jobs
YOLO-detect-buoys/requirements.txt	Moved requirements file to project directory
YOLO-detect-buoys/main.py	Updated to use Unix-style paths and added model export
YOLO-detect-buoys/Job.slurm	SLURM configuration for buoy detection training
.github/workflows/pylint.yml	Updated to reference new requirements.txt location

Comments suppressed due to low confidence (2)

YOLO-detect-buoys/Job.slurm:1

• Invalid SLURM time format '999:99:99'. The time format should be DD-HH:MM:SS, HH:MM:SS, or MM:SS with valid values (e.g., hours 0-23, minutes/seconds 0-59).
  YOLO-detect-buoys/Job.slurm:1
• The script references 'train.py' but the main entry point in this directory is 'main.py'. This should be 'python3 main.py' or 'python3 -m YOLO-detect-buoys'.

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[Copilot]

Pull request overview

Copilot reviewed 17 out of 25 changed files in this pull request and generated 9 comments.

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[Copilot]

Pull request overview

Copilot reviewed 17 out of 25 changed files in this pull request and generated 8 comments.

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Pull request overview

Copilot reviewed 19 out of 29 changed files in this pull request and generated 1 comment.

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[Copilot]

Line 29 calls torch.cuda.get_device_name(0) without checking if GPU 0 exists. If the system has GPUs but not at index 0, or CUDA_VISIBLE_DEVICES is set differently, this could fail with an IndexError. Consider using torch.cuda.get_device_name(DEVICE) or checking the device count first.

Suggested change

	print("Using GPU:", torch.cuda.get_device_name(0))
	device_count = torch.cuda.device_count()
	if isinstance(DEVICE, int) and 0 <= DEVICE < device_count:
	print("Using GPU:", torch.cuda.get_device_name(DEVICE))
	else:
	print("Using CUDA device configuration:", DEVICE)