Detection result shifted when export model to onnx

I try to convert model to onnx to deploy by opencv, on pt weight it can detect, but when convert to onnx the detection result shift this is detect result when i try to detect home button and select folder button of tree size free software [url=https://anh.moe/view/f8KTwx]https://anh.moe/view/f8KTwx [/url] `from ultralytics import YOLOv10 import cv2 import glob import os model_path = "runs_1/detect/train/weights/best.onnx" video_path = "Image" save_video_path = "output/output.avi" model = YOLOv10(model_path) label = ["Home", "Select"] video = True image = False path = glob.glob(video_path) for p in path: for filename in os.listdir(p): full_path = os.path.join(p, filename) print(full_path) if filename.contains("jpg"): model.predict(full_path, save= True,conf= 0.5) frame_Full = cv2.imread(full_path) frame = cv2.resize(frame_Full, (640, 640)) frame_cp = frame.copy() # frame_cp = frame_cp[224:868, 520:1140] w = 640 h=640 results = model(source=frame_cp, conf=0.1) for r in results: if r.boxes is None: print('None') continue for result in r.boxes.data: result = result.cpu().detach().numpy() boxes = result[:4] print(boxes) x, y, bw, bh = boxes left = int((x+13)1920/640) top = int(y1080/640) right = int((x+bw/2)*1920/640) bottom = int((y+bh/2)1080/640) print('left, top, right, bottom') print(filename) print(left, top, right, bottom) #left, top, right, bottom = boxes classes = int(result[5]) scores = result[4] cv2.rectangle(frame_Full, (int(left), int(top)), (int(right), int(bottom)), color=[255, 255, 0], thickness=2) cv2.putText(frame_Full, f"{label[classes]}" + "_{:.2f}%".format(scores100), (int(left), int(top)), cv2.FONT_HERSHEY_SIMPLEX, 1, color=[255, 255, 0], thickness=2) # cv2.imwrite((p[:-4]+'_org.jpg'), frame) cv2.imwrite("Test/"+filename, frame_Full)

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