Detect vehicle license plates
Project description
wheresmycar
First attempt at utilizing YOLOv8 model for vehicle number plate detection.
[!NOTE] This project is for education and skills presentation purposes.
Motivation
Gain practical knowledge with machine learning technologies in real-world example.
The main goal was to gain hands-on experience in machine learning project utilizing PyTorch library and several technologies to improve software engineering skills.
About the project
Small Python package providing a class for object detection, utilizing YOLOv8 model which was trained to detect number plates on vehicles.
Documentation
plate_detector
plate_detector module
PlateDetector Objects
class PlateDetector()
Class for Vehicle Number Plate Detection based on pretrained YOLOv8 model.
load_model
def load_model(device: str) -> YOLO
Function to load pretrained model. params:
- device : device on which the model should run returns:
- <ultralytics.YOLO>: pretrained YOLOv8 model
model
@property
def model() -> YOLO
Access pretrained model returns:
- <ultralytics.YOLO>: pretrained YOLOv8 model
get_device
def get_device(enable_cuda: bool) -> str
Gets target device for inference. params:
- enable_cude : if True, will return cuda if available returns:
- either cuda or cpu
detect
def detect(target_path: str, conf: float = 0.5, **kwargs) -> Results
Get predictions on given input. params:
- target_path : path to directory with images or image's file path
- conf : minimum confidence threshold for detection returns:
- <ultralytics.engine.results.Results>: inference results
Project details
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