diff --git a/study_python/tkinter-opencv/main.py b/study_python/tkinter-opencv/main.py
new file mode 100644
index 0000000..e4439b6
--- /dev/null
+++ b/study_python/tkinter-opencv/main.py
@@ -0,0 +1,176 @@
+import cv2
+import numpy as np
+import os
+from tkinter import Tk
+from tkinter.filedialog import askopenfilename
+
+# 创建一个 Tkinter 根窗口
+root = Tk()
+root.withdraw()
+
+# 打开文件对话框，选择图片文件
+filename = askopenfilename(title='选择图片', filetypes=[('Image Files', ('*.jpg', '*.jpeg', '*.png', '*.bmp'))])
+
+# 检查是否选择了文件
+if filename:
+    # 读取选中的图片文件
+    image = cv2.imread(filename)
+
+    # 定义全局变量
+    points = []
+    completed = False
+    extracted_image = None
+
+    # 定义鼠标回调函数
+    def mouse_callback(event, x, y, flags, param):
+        global points, completed, extracted_image
+
+        if event == cv2.EVENT_LBUTTONDOWN:
+            # 存储点击的坐标
+            points.append((x, y))
+
+            # 绘制已选择的点
+            cv2.circle(image, (x, y), 5, (0, 0, 255), -1)
+
+            # 绘制连接的线段
+            if len(points) > 1:
+                cv2.line(image, points[-2], points[-1], (0, 0, 255), 5)
+
+            # 绘制最后一个点与第一个点的连线
+            if len(points) == 4:
+                cv2.line(image, points[-1], points[0], (0, 0, 255), 5)
+                completed = True
+
+    # 创建窗口并注册鼠标回调函数
+    cv2.namedWindow('image')
+    cv2.setMouseCallback('image', mouse_callback)
+
+    while True:
+        # 显示图像
+        cv2.imshow('image', image)
+
+        # 按下 'Esc' 键退出循环
+        if cv2.waitKey(1) == 27:
+            break
+
+        # 检查是否成功获取四边形
+        if completed:
+            # 创建与原图像大小相同的掩膜图像
+            mask = np.zeros_like(image[:, :, 0])
+
+            # 使用填充多边形函数将四边形区域设置为白色
+            cv2.fillPoly(mask, [np.array(points)], 255)
+
+            # 将掩膜应用到原图像上，提取方框内的内容
+            extracted_image = cv2.bitwise_and(image, image, mask=mask)
+
+            # 将方框外的像素值设置为0
+            extracted_image[np.where(extracted_image == 0)] = 0
+
+            # 显示提取的图像
+            cv2.imshow('extracted_image', extracted_image)
+
+            # 获取文件名和扩展名
+            file_dir = os.path.dirname(filename)
+            file_name = os.path.basename(filename)
+            file_name, file_ext = os.path.splitext(file_name)
+
+            # 构建新的文件名
+            extracted_image_file_name = os.path.join(file_dir, file_name + "_boundary" + file_ext)
+
+            # 保存提取后的图像
+            cv2.imwrite(extracted_image_file_name, extracted_image)
+
+            # 转换提取后的图像到 LAB 色彩空间
+            lab_image = cv2.cvtColor(extracted_image, cv2.COLOR_BGR2LAB)
+            segmented_image = []
+            combined_image = []
+
+            # 定义鼠标事件回调函数
+            def mouse_callback1(event, x, y, flags, param):
+                global segmented_image, combined_image
+
+                if event == cv2.EVENT_LBUTTONDOWN:
+                    if combined_image[y, x, 0] == 0 and combined_image[y, x, 1] == 0 and combined_image[y, x, 2] == 0:
+                        # 创建临时变量用于处理连通域
+                        segmented_image[y-8:y+8, x-8:x+8] = 255
+                        colored_segmented_image = cv2.cvtColor(segmented_image, cv2.COLOR_GRAY2BGR)
+                        combined_image = cv2.bitwise_and(extracted_image, colored_segmented_image)
+                        cv2.imshow('segmented_image', combined_image)
+
+                        leaf_image_file_name = os.path.join(file_dir, file_name + "_leaf" + file_ext)
+                        cv2.imwrite(leaf_image_file_name, combined_image)
+                        nonzero_pixels_b = np.count_nonzero(extracted_image[:, :, 0])
+                        nonzero_pixels_leaf = np.count_nonzero(combined_image[:, :, 0])
+                        result_file = os.path.join(file_dir, file_name + "_result.txt")
+                        file = open(result_file, 'w')
+                        file.truncate(0)
+                        file.write('采样框像素点数为' + str(nonzero_pixels_b))
+                        file.write('采样框内绿叶像素点数为' + str(nonzero_pixels_leaf))
+                        file.close()
+
+            # 定义滑动条的回调函数
+            def on_trackbar(value):
+                global segmented_image
+                global combined_image
+                lower_th = cv2.getTrackbarPos('L', 'segmented_image')
+                upper_th = cv2.getTrackbarPos('A', 'segmented_image')
+                v_value = cv2.getTrackbarPos('B', 'segmented_image')
+
+                # 根据滑动条的值创建阈值范围
+                lower = np.array([lower_th, upper_th, v_value], dtype=np.uint8)
+                upper = np.array([255, 255, 255], dtype=np.uint8)
+
+                # 对 LAB 图像进行阈值分割
+                segmented_image = cv2.inRange(lab_image, lower, upper)
+
+                # 反转二值图像
+                segmented_image = cv2.bitwise_not(segmented_image)
+
+                # 将二值图像转换为彩色图像
+                colored_segmented_image = cv2.cvtColor(segmented_image, cv2.COLOR_GRAY2BGR)
+                # 进行位逻辑与操作，将彩色分割图像与提取图像进行合并
+                combined_image = cv2.bitwise_and(extracted_image, colored_segmented_image)
+                # 显示合并后的图像
+                cv2.imshow('segmented_image', combined_image)
+                leaf_image_file_name = os.path.join(file_dir, file_name + "_leaf" + file_ext)
+                cv2.imwrite(leaf_image_file_name, combined_image)
+                nonzero_pixels_b = np.count_nonzero(extracted_image[:, :, 0])
+                nonzero_pixels_leaf = np.count_nonzero(combined_image[:, :, 0])
+                result_file = os.path.join(file_dir, file_name + "_result.txt")
+                file = open(result_file, 'w')
+                file.truncate(0)
+                file.write('采样框像素点数为' + str(nonzero_pixels_b))
+                file.write('采样框内绿叶像素点数为' + str(nonzero_pixels_leaf))
+                file.close()
+
+            # 创建窗口用于显示分割结果
+            cv2.namedWindow('segmented_image')
+            cv2.setMouseCallback('segmented_image', mouse_callback1)
+
+            # 创建滑动条
+            cv2.createTrackbar('L', 'segmented_image', 0, 255, on_trackbar)
+            cv2.createTrackbar('A', 'segmented_image', 0, 255, on_trackbar)
+            cv2.createTrackbar('B', 'segmented_image', 0, 255, on_trackbar)
+
+            # 初始化滑动条的值
+            cv2.setTrackbarPos('L', 'segmented_image', 0)
+            cv2.setTrackbarPos('A', 'segmented_image', 115)
+            cv2.setTrackbarPos('B', 'segmented_image', 0)
+
+            while True:
+                # 按下 'Esc' 键退出循环
+                if cv2.waitKey(1) == 27:
+                    break
+
+            # 重置标志和列表，以便选择下一个方框
+            completed = False
+            points.clear()
+
+            # 退出循环
+            break
+
+    # 释放窗口和销毁所有窗口
+    cv2.destroyAllWindows()
+else:
+    print("未选择图像文件")
diff --git a/study_python/tkinter-opencv/main.spec b/study_python/tkinter-opencv/main.spec
new file mode 100644
index 0000000..e03e1a6
--- /dev/null
+++ b/study_python/tkinter-opencv/main.spec
@@ -0,0 +1,44 @@
+# -*- mode: python ; coding: utf-8 -*-
+
+
+a = Analysis(
+    ['main.py'],
+    pathex=[],
+    binaries=[],
+    datas=[],
+    hiddenimports=[],
+    hookspath=[],
+    hooksconfig={},
+    runtime_hooks=[],
+    excludes=[],
+    noarchive=False,
+    optimize=0,
+)
+pyz = PYZ(a.pure)
+
+exe = EXE(
+    pyz,
+    a.scripts,
+    [],
+    exclude_binaries=True,
+    name='main',
+    debug=False,
+    bootloader_ignore_signals=False,
+    strip=False,
+    upx=True,
+    console=True,
+    disable_windowed_traceback=False,
+    argv_emulation=False,
+    target_arch=None,
+    codesign_identity=None,
+    entitlements_file=None,
+)
+coll = COLLECT(
+    exe,
+    a.binaries,
+    a.datas,
+    strip=False,
+    upx=True,
+    upx_exclude=[],
+    name='main',
+)
diff --git a/study_python/tkinter-opencv/requirements.txt b/study_python/tkinter-opencv/requirements.txt
new file mode 100644
index 0000000..c394276
--- /dev/null
+++ b/study_python/tkinter-opencv/requirements.txt
@@ -0,0 +1,2 @@
+numpy==2.0.0
+opencv_python==4.10.0.84