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Oleksandr Bezdieniezhnykh 142c6c4de8 Refactor constants management to use Pydantic BaseModel for configuration

- Replaced module-level path variables in constants.py with a structured Pydantic Config class.
- Updated all relevant modules (train.py, augmentation.py, exports.py, dataset-visualiser.py, manual_run.py) to access paths through the new config structure.
- Fixed bugs related to image processing and model saving.
- Enhanced test infrastructure to accommodate the new configuration approach.

This refactor improves code maintainability and clarity by centralizing configuration management.

2026-03-27 18:18:30 +02:00

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Module: dataset-visualiser

Purpose

Interactive tool for visually inspecting annotated images from datasets or the processed folder, displaying bounding boxes with class colors.

Public Interface

Function	Signature	Description
`visualise_dataset`	`()`	Iterates images in a specific dataset folder, shows each with annotations. Waits for keypress.
`visualise_processed_folder`	`()`	Shows images from the processed folder with annotations.

Internal Logic

visualise_dataset(): Hardcoded to a specific dataset date (2024-06-18), iterates from index 35247 onward. Reads image + labels, calls ImageLabel.visualize(), waits for user input to advance.
visualise_processed_folder(): Lists all processed images, shows the first one.
Both functions use read_labels() imported from a preprocessing module which does not exist in the codebase — this is a broken import.

Dependencies

constants — directory paths (datasets_dir, prefix, processed_*)
dto/annotationClass — AnnotationClass for class colors
dto/imageLabel — ImageLabel for visualization
preprocessing — MISSING MODULE (read_labels function)
cv2 (external), matplotlib (external), os, pathlib (stdlib)

Consumers

None (standalone script).

Data Models

Uses ImageLabel, AnnotationClass.

Configuration

Hardcoded dataset path and start index.

External Integrations

Filesystem I/O, matplotlib interactive display.

Security

None.

Tests