Why my code just identify 3 of the 4 numbers correctly?

Here I make an outline in the numbers

And here I try to identify correctly the numbers

import cv2
import numpy as np
import matplotlib.pyplot as plt
from tensorflow.keras.datasets import mnist

def segment_digits(image):
    _, thresh = cv2.threshold(image, 128, 255, cv2.THRESH_BINARY_INV)
    contours, _ = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
    
    digits = []
    for cnt in contours:
        x, y, w, h = cv2.boundingRect(cnt)
        if h > 20 and w > 10:  
            digit = image[y:y+h, x:x+w]
            digit = cv2.resize(digit, (28, 28))
            digits.append((x, digit))
    
    digits = sorted(digits, key=lambda d: d[0])
    
    return [d[1] for d in digits]

def train_knn_model():
    (x_train, y_train), (_, _) = mnist.load_data()
    x_train = x_train.reshape((x_train.shape[0], 28 * 28)).astype(np.float32)
    y_train = y_train.astype(np.float32)

    knn = cv2.ml.KNearest_create()
    knn.train(x_train, cv2.ml.ROW_SAMPLE, y_train)
    return knn

def predict_digit(model, digit):
    sample = digit.reshape((1, 784)).astype(np.float32)
    _, result, _, _ = model.findNearest(sample, k=1)
    return int(result[0][0])

image_path = 'digits_image.png'
image = cv2.imread(image_path, cv2.IMREAD_GRAYSCALE)

if image is None:
    print("Erro ao carregar a imagem.")
    exit()

digits = segment_digits(image)

plt.subplot(1, 2, 1)
plt.imshow(image, cmap='gray')
plt.title("Imagem Original")

_, thresh = cv2.threshold(image, 128, 255, cv2.THRESH_BINARY_INV)
contours, _ = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
contoured_image = cv2.drawContours(image.copy(), contours, -1, (255, 0, 0), 2)

plt.subplot(1, 2, 2)
plt.imshow(contoured_image, cmap='gray')
plt.title("Imagem com Contornos")

plt.show()

if len(digits) != 4:
    print(f"Não foram encontrados 4 dígitos na imagem. Foram encontrados {len(digits)} dígitos.")
    exit()

knn_model = train_knn_model()

predicted_digits = [predict_digit(knn_model, digit) for digit in digits]

for i, digit in enumerate(digits):
    plt.subplot(1, 4, i + 1)
    plt.imshow(digit, cmap='gray')
    plt.title(predicted_digits[i])
    plt.axis('off')

plt.show()

print("Predicted digits:", predicted_digits)

I try use tensor flow, and train a model to solve the problem, but I’m not able to solve this only problem. Actualy, a dunno how to train correctly a model, so a need help, pls, and thx