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https://github.com/azaion/ai-training.git
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Oleksandr Bezdieniezhnykh
142c6c4de8
- 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.
1.6 KiB
1.6 KiB
Module: inference/dto
Purpose
Data transfer objects for the inference subsystem: Detection, Annotation, and a local copy of AnnotationClass/WeatherMode.
Public Interface
Detection
| Field | Type | Description |
|---|---|---|
x |
float | Normalized center X |
y |
float | Normalized center Y |
w |
float | Normalized width |
h |
float | Normalized height |
cls |
int | Class ID |
confidence |
float | Detection confidence score |
overlaps(det2, iou_threshold) -> bool |
method | IoU-based overlap check |
Annotation
| Field | Type | Description |
|---|---|---|
frame |
numpy.ndarray | Video frame image |
time |
int/float | Timestamp in the video |
detections |
list[Detection] | Detected objects in this frame |
AnnotationClass (duplicate)
Same as dto/annotationClass.AnnotationClass but with an additional opencv_color field (BGR tuple). Reads from classes.json relative to inference/ parent directory.
WeatherMode (duplicate)
Same as dto/annotationClass.WeatherMode.
Internal Logic
Detection.overlaps()computes IoU between two bounding boxes and returns True if above threshold.AnnotationClasshere addsopencv_coloras a pre-computed BGR tuple from the hex color for efficient OpenCV rendering.
Dependencies
json,enum,os.path(stdlib)
Consumers
inference/inference
Data Models
Detection, Annotation, AnnotationClass, WeatherMode.
Configuration
Reads classes.json from project root.
External Integrations
None.
Security
None.
Tests
None.