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35 lines
1008 B
Python
35 lines
1008 B
Python
from ultralytics import YOLO
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from PIL import Image
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from transformers import TrOCRProcessor, VisionEncoderDecoderModel
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import os
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os.chdir(
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"C:/Users/celma/OneDrive - Hanze/School/periode 1.4/IOT/YOLO11/License Plate Recognition.v11i.yolov11"
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)
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model = YOLO("license_plate_detector.pt")
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names = model.names
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results = model.predict("test/images/000i.jpg", show=False, save=False)
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img = Image.open("test/images/000i.jpg")
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boxes = results[0].boxes.xyxy.cpu().tolist()
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clss = results[0].boxes.cls.cpu().tolist()
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print(boxes)
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if boxes is not None:
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for box, cls in zip(boxes, clss):
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crop_obj = boxes[int(box[1]) : int(box[3]) + int(box[0]) : int(box[2])]
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cropped_img = img.crop((int(box[0]), int(box[1]), int(box[2]), int(box[3])))
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cropped_img.show()
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image = cropped_img.convert("RGB")
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pixel_values = processor(images=image, return_tensors="pt").pixel_values
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generated_ids = model.generate(pixel_values)
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text = processor.batch_decode(generated_ids, skip_special_tokens=True)[0]
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print(text)
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