letter_recognition.data データセットを使用して OpenCV-Python で単純な数字認識を実装するにはどうすればよいですか?

import numpy as np
import cv2

# Load training data
samples = np.loadtxt('letter_recognition.data', np.float32, delimiter=',', converters={0: lambda ch: ord(ch) - ord('A')})
responses = samples[:, 0]
samples = samples[:, 1:]

# Create KNearest classifier
model = cv2.KNearest()

# Train the classifier
model.train(samples, responses)

# Load test image
test_image = cv2.imread('test_image.png')

# Preprocess the image
gray = cv2.cvtColor(test_image, cv2.COLOR_BGR2GRAY)
thresh = cv2.adaptiveThreshold(gray, 255, 1, 1, 11, 2)

# Extract digits
contours, hierarchy = cv2.findContours(thresh, cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE)

digits = []

for cnt in contours:
    if cv2.contourArea(cnt) > 50:
        [x, y, w, h] = cv2.boundingRect(cnt)
        roi = thresh[y:y + h, x:x + w]
        roismall = cv2.resize(roi, (10, 10))
        digits.append(roismall)

# Predict labels for digits
results = model.find_nearest(np.array(digits), 10)
labels = [chr(ch + ord('A')) for ch in results[0]]

# Display recognized digits on the image
for i, label in enumerate(labels):
    cv2.putText(test_image, str(label), (digits[i][0], digits[i][1]), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 0))

cv2.imshow('Recognized Digits', test_image)
cv2.waitKey(0)