仅检测图像中最左侧的框

我有一张包含手机品牌名称的 JPG 图像：

现在我想通过 python 脚本检测每个单词的第一个字符，
为此我编写了以下 python 脚本：

import cv2
import numpy as np
from tkinter import Tk, Canvas, Frame, Scrollbar, BOTH, VERTICAL, HORIZONTAL
from PIL import Image, ImageTk

# Function to draw rectangles around shapes and display using Tkinter
def draw_rectangles(image_path):
    # Create a Tkinter window to display the image
    root = Tk()
    root.title("Image with Left-Most Rectangles Only")

    # Load the image
    image = cv2.imread(image_path)
    # Convert the image to grayscale
    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

    # Apply adaptive thresholding to get better separation of text
    thresh = cv2.adaptiveThreshold(
        gray, 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY_INV, 11, 2
    )

    # Find contours in the binary image
    contours, _ = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)

    # Dictionary to store contours grouped by Y-coordinate ranges
    contours_by_y = {}

    # Sort contours by X-coordinate to ensure we pick the left-most character first
    sorted_contours = sorted(contours, key=lambda c: cv2.boundingRect(c)[0])

    # Group contours by their Y coordinate to keep only the left-most rectangle per Y range
    for contour in sorted_contours:
        x, y, w, h = cv2.boundingRect(contour)
        if w > 15 and h > 15:  # Adjust the size filter to remove small artifacts
            aspect_ratio = w / float(h)
            # Ensure the aspect ratio is within the typical range of letters
            if 0.2 < aspect_ratio < 5:
                y_range = y // 20  # Group by a smaller Y coordinate range for better separation

                # Check if the current rectangle is more left-most in X within its Y range
                if y_range not in contours_by_y:
                    contours_by_y[y_range] = (x, y, w, h)  # Store the first contour found in this range
                else:
                    # Compare and keep the left-most (smallest X) rectangle
                    current_x, _, _, _ = contours_by_y[y_range]
                    # Check distance between new contour and the existing one to avoid close detection
                    if x < current_x and (x - current_x) > 20:  # Distance threshold to filter out close contours
                        contours_by_y[y_range] = (x, y, w, h)

    # Draw only the left-most rectangles
    for (x, y, w, h) in contours_by_y.values():
        cv2.rectangle(image, (x, y), (x + w, y + h), (0, 0, 255), 2)  # Red color in BGR

    # Convert the image to RGB (OpenCV uses BGR by default)
    image_rgb = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)

    # Convert the image to a format Tkinter can use
    image_pil = Image.fromarray(image_rgb)
    image_tk = ImageTk.PhotoImage(image_pil)

    # Create a frame for the Canvas and scrollbars
    frame = Frame(root)
    frame.pack(fill=BOTH, expand=True)

    # Create a Canvas widget to display the image
    canvas = Canvas(frame, width=image_tk.width(), height=image_tk.height())
    canvas.pack(side="left", fill="both", expand=True)

    # Add scrollbars to the Canvas
    v_scrollbar = Scrollbar(frame, orient=VERTICAL, command=canvas.yview)
    v_scrollbar.pack(side="right", fill="y")

    h_scrollbar = Scrollbar(frame, orient=HORIZONTAL, command=canvas.xview)
    h_scrollbar.pack(side="bottom", fill="x")

    canvas.configure(yscrollcommand=v_scrollbar.set, xscrollcommand=h_scrollbar.set)
    canvas.create_image(0, 0, anchor="nw", image=image_tk)
    canvas.config(scrollregion=canvas.bbox("all"))

    # Keep a reference to the image to prevent garbage collection
    canvas.image = image_tk

    root.mainloop()

# Path to your image
image_path = r"E:\Desktop\mobile_brands\ORG_027081-Recovered.jpg"

# Call the function
draw_rectangles(image_path)

但我不知道为什么它效果不好。这个脚本的准确率是 90%。例如在上图中，它检测到“Samsung”中的“a”字符

我的脚本问题在哪里？
我该如何解决这个问题？
也许通过 Y 和 X 坐标无法检测图像中最左边的框。
请注意，我不想使用 OCR