Failed to execute script due to unhandled exception the path doesnt exist

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so I want to change my code file from the .py extension to .exe. Well after finishing to .exe when i try to opened there is error like this "the path doesn't exist" that's why can anyone explain? thank you in advance ????

error message :
Traceback (most recent call last):   
File test.py, line 9, in <module>   
File cvzone\HandTrackingModule.py, line 33, in __init__   
File mediapipe\python\solutions\hands.py, line 114, in __init__   
File mediapipe\python\solution_base.py, line 263, in __init__ 
FileNotFoundError: The path does not exist.

i use pyinstaller to convert python to executable file. The command is --onefile -w {script name}.

my code

from tkinter import Label
import cv2
from cvzone.HandTrackingModule import HandDetector
from cvzone.ClassificationModule import Classifier
import numpy as np
import math

capture = cv2.VideoCapture(0, cv2.CAP_DSHOW)
detector = HandDetector(maxHands=1)
Detector = HandDetector("C:/Users/W10/Documents/Handsign/cvzone/HandTrackingModule.py")
Classifier = Classifier("C:/Users/W10/Documents/Handsign/Model/keras_model.h5", "C:/Users/W10/Documents/Handsign/Model/labels.txt")

offset = 20
imgSize = 300

counter = 0

labels = ["A", "B", "C","D", "E", "Halo", "Aku", "Nama", "I", "F"]

while True:
    success, img = capture.read()
    imgOutput = img.copy()
    hands, img = detector.findHands(img)
    if hands:
        hand = hands[0]
        x, y, w, h = hand['bbox']
        imgWhite = np.ones((imgSize, imgSize, 3), np.uint8) * 255
        imgCrop = img[y - offset:y + h + offset, x - offset:x + w + offset]

        imgCropShape = imgCrop.shape

        aspectRatio = h / w

        if aspectRatio > 1:
            k = imgSize / h
            wCal = math.ceil(k * w)
            imgResize = cv2.resize(imgCrop, (wCal, imgSize))
            imgResizeShape = imgResize.shape
            wGap = math.ceil((imgSize - wCal) / 2)
            imgWhite[:, wGap:wCal + wGap] = imgResize
            prediction, index = Classifier.getPrediction(imgWhite, draw = False)
            print(prediction, index)

        else:
            k = imgSize / w
            hCal = math.ceil(k * h)
            imgResize = cv2.resize(imgCrop, (imgSize, hCal))
            imgResizeShape = imgResize.shape
            hGap = math.ceil((imgSize - hCal) / 2)
            imgWhite[hGap:hCal + hGap, :] = imgResize
            prediction, index = Classifier.getPrediction(imgWhite, draw = False)

        cv2.rectangle(imgOutput, (x - offset, y - offset-50), (x - offset+90, y - offset-50+50), (255, 0, 255), cv2.FILLED)
        cv2.putText(imgOutput, labels[index], (x,y-30), cv2.FONT_HERSHEY_COMPLEX, 1.7,(255,255,255), 2)
        cv2.rectangle(imgOutput,(x-offset,y-offset),(x+w+offset,y+h+offset),(255,0,255), 4)

        cv2.imshow("ImageCrop", imgCrop)
        cv2.imshow("ImageWhite", imgWhite)

    cv2.imshow("Image", imgOutput)
    cv2.waitKey(5)
pythonpyinstallerexe