YOLOV8: how to save the output of model

Question

this is the code

from ultralytics import YOLO
license_plate_detector = YOLO('./model/best.pt')
license_plates = license_plate_detector('./42.jpg')

and this the output

640x608 1 number-plate, 342.0ms
Speed: 12.4ms preprocess, 342.0ms inference, 3.0ms postprocess per image at shape (1, 3, 640, 608)

i want to convert this output to image and save it to use with esayocr

the class don't have any save method so how to do this

Answer 1

I think, it will helps you.

from PIL import Image
from ultralytics import YOLO
import easyocr

license_plate_detector = YOLO('./model/best.pt')

input_image = Image.open('./42.jpg')

detections = license_plate_detector(input_image)

license_plate_boxes = detections[0].boxes.data.cpu().numpy()

reader = easyocr.Reader(['en'])

for i, box in enumerate(license_plate_boxes):
    x1, y1, x2, y2, conf, cls = box
    license_plate = input_image.crop((x1, y1, x2, y2))
    
    plate_filename = f'license_plate_{i}.jpg'
    license_plate.save(plate_filename)

    results = reader.readtext(plate_filename)
    print(f"License Plate {i+1} Text: {results[0][1]}")