yolov8-onnx 1.0.4

YoloV8 Package Tools

YOLOV8 ONNX

Description

This package is compatible with YoloV8 for object detection program, using ONNX format model (CPU & GPU speed can be x2 Times Faster). This code is referenced from this awesome repo.

Usage

Step 1: Convert your pre-trained model to ONNX format.

from ultralytics import YOLO

# Load your pre-trained model
model = YOLO('your-trained-model.pt')

# Export the model
model.export(format='onnx', 
            batch=1, 
            device='cpu', 
            simplify=True, 
            imgsz=640, 
            dynamic=True)

Step 2: Use in your code.

from yolov8_onnx import DetectEngine

engine = DetectEngine(model_path= str | 'your-model.onnx',
                        image_size = int | 640,
                        conf_thres= float | 0.5, 
                        iou_thres= float | 0.1)

output = engine(image) # cv2 image

Note: akaOCR (Transform documents into useful data with AI-based IDP - Intelligent Document Processing) - helps make inefficient manual entry a thing of the past—and reliable data insights a thing of the present. Details at: https://app.akaocr.io