parent
490030fb43
commit
4f9d56b57b
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import tkinter as tk
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from tkinter import filedialog, messagebox
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from tkinter import Toplevel
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from PIL import Image, ImageTk
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import numpy as np
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import math
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import cv2
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import os
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img_path = "" # 全局变量，用于存储图像路径
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src = None # 全局变量，用于存储已选择的图像
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X = None # 用于存储第一张图像
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Y = None # 用于存储第二张图像
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img_label = None # 全局变量，用于存储显示选择的图片的标签
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GeomeanWin = None
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SortstatWin = None
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SelectWin = None
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def select_image(root):
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global img_path, src, img_label, edge
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img_path = filedialog.askopenfilename(filetypes=[("Image files", "*.jpg;*.png;*.jpeg;*.bmp")])
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if img_path:
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# 确保路径中的反斜杠正确处理，并使用 UTF-8 编码处理中文路径
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img_path_fixed = os.path.normpath(img_path)
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# 图像输入
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src_temp = cv2.imdecode(np.fromfile(img_path_fixed, dtype=np.uint8), cv2.IMREAD_UNCHANGED)
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if src_temp is None:
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messagebox.showerror("错误", "无法读取图片，请选择有效的图片路径")
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return
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src = cv2.cvtColor(src_temp, cv2.COLOR_BGR2RGB)
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# 检查 img_label 是否存在且有效
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if img_label is None or not img_label.winfo_exists():
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img_label = tk.Label(root)
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img_label.pack(side=tk.TOP, pady=10)
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img = Image.open(img_path)
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img.thumbnail((160, 160))
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img_tk = ImageTk.PhotoImage(img)
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img_label.configure(image=img_tk)
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img_label.image = img_tk
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# 定义 edge 变量为 PIL.Image 对象，以便稍后保存
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edge = Image.fromarray(src)
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else:
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messagebox.showerror("错误", "没有选择图片路径")
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def show_selected_image(root):
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global img_label
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img_label = tk.Label(root)
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img_label.pack(side=tk.TOP, pady=10)
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img = Image.open(img_path)
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img.thumbnail((160, 160))
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img_tk = ImageTk.PhotoImage(img)
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img_label.configure(image=img_tk)
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img_label.image = img_tk
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def changeSize(event, img, LabelPic):
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img_aspect = img.shape[1] / img.shape[0]
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new_aspect = event.width / event.height
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if new_aspect > img_aspect:
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new_width = int(event.height * img_aspect)
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new_height = event.height
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else:
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new_width = event.width
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new_height = int(event.width / img_aspect)
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resized_image = cv2.resize(img, (new_width, new_height))
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image1 = ImageTk.PhotoImage(Image.fromarray(resized_image))
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LabelPic.image = image1
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LabelPic['image'] = image1
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def savefile():
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global edge
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filename = filedialog.asksaveasfilename(defaultextension=".jpg", filetypes=[("JPEG files", "*.jpg"), ("PNG files", "*.png"), ("BMP files", "*.bmp")])
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if not filename:
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return
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# 确保 edge 变量已定义
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if edge is not None:
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try:
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edge.save(filename)
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messagebox.showinfo("保存成功", "图片保存成功！")
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except Exception as e:
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messagebox.showerror("保存失败", f"无法保存图片: {e}")
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else:
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messagebox.showerror("保存失败", "没有图像可保存")
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#几何均值滤波
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def geo_mean_filter(root):
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global src, GeomeanWin, edge
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# 判断是否已经选取图片
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if src is None:
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messagebox.showerror("错误", "没有选择图片！")
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return
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image = cv2.cvtColor(src, cv2.COLOR_BGR2GRAY)
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# 待输出的图片
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output = np.zeros(image.shape, np.uint8)
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# 遍历图像，进行均值滤波
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for i in range(image.shape[0]):
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for j in range(image.shape[1]):
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# 计算均值,完成对图片src的几何均值滤波
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ji = 1.0
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# 遍历滤波器内的像素值
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for k in range(-1, 2):
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if 0 <= j + k < image.shape[1]:
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ji *= image[i, j + k]
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# 滤波器的大小为1*3
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geom_mean = math.pow(ji, 1 / 3.0)
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output[i, j] = int(geom_mean)
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# 更新 edge 变量
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edge = Image.fromarray(output)
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# 创建Toplevel窗口
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try:
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GeomeanWin.destroy()
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except Exception:
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print("NVM")
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finally:
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GeomeanWin = Toplevel()
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GeomeanWin.attributes('-topmost', True)
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GeomeanWin.geometry("720x300")
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GeomeanWin.resizable(True, True) # 可缩放
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GeomeanWin.title("几何均值滤波结果")
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# 显示图像
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LabelPic = tk.Label(GeomeanWin, text="IMG", width=360, height=240)
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image = ImageTk.PhotoImage(Image.fromarray(output))
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LabelPic.image = image
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LabelPic['image'] = image
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LabelPic.bind('<Configure>', lambda event: changeSize(event, output, LabelPic))
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LabelPic.pack(fill=tk.BOTH, expand=tk.YES)
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# 添加保存按钮
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btn_save = tk.Button(GeomeanWin, text="保存", bg='#add8e6', fg='black', font=('Helvetica', 14), width=20,
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command=savefile)
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btn_save.pack(pady=10)
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return
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#排序统计类滤波
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def sort_stat_filter(root):
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global src, SortstatWin, combined, edge
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# 判断是否已经选取图片
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if src is None:
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messagebox.showerror("错误", "没有选择图片！")
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return
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image = cv2.cvtColor(src, cv2.COLOR_BGR2GRAY)
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# 待输出的图片
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output_max = np.zeros(image.shape, np.uint8)
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output_median = np.zeros(image.shape, np.uint8)
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output_min = np.zeros(image.shape, np.uint8)
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for i in range(image.shape[0]):
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for j in range(image.shape[1]):
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# 用于存储3x3邻域像素值
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neighbors = []
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for m in range(-1, 2):
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for n in range(-1, 2):
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if 0 <= i + m < image.shape[0] and 0 <= j + n < image.shape[1]:
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neighbors.append(image[i + m, j + n])
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# 最大值滤波
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output_max[i, j] = max(neighbors)
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# 中值滤波
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output_median[i, j] = np.median(neighbors)
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# 最小值滤波
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output_min[i, j] = min(neighbors)
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combined = np.hstack((output_max, output_median, output_min))
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# 更新 edge 变量
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edge = Image.fromarray(combined)
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# 创建Toplevel窗口
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try:
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SortstatWin.destroy()
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except Exception:
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print("NVM")
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finally:
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SortstatWin = Toplevel()
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SortstatWin.attributes('-topmost', True)
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SortstatWin.geometry("720x300")
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SortstatWin.resizable(True, True) # 可缩放
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SortstatWin.title("排序统计类滤波结果")
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# 显示图像
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LabelPic = tk.Label(SortstatWin, text="IMG", width=360, height=240)
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image = ImageTk.PhotoImage(Image.fromarray(combined))
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LabelPic.image = image
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LabelPic['image'] = image
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LabelPic.bind('<Configure>', lambda event: changeSize(event, combined, LabelPic))
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LabelPic.pack(fill=tk.BOTH, expand=tk.YES)
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# 添加保存按钮
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btn_save = tk.Button(SortstatWin, text="保存", bg='#add8e6', fg='black', font=('Helvetica', 14), width=20,
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command=savefile)
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btn_save.pack(pady=10)
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return
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#选择性滤波
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def selective_filter(root):
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global src, SelectWin, combined, edge
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# 判断是否已经选取图片
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if src is None:
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messagebox.showerror("错误", "没有选择图片！")
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return
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image = cv2.cvtColor(src, cv2.COLOR_BGR2GRAY)
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# 待输出的图片
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output_low_pass = np.zeros(image.shape, np.uint8)
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output_high_pass = np.zeros(image.shape, np.uint8)
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output_band_pass = np.zeros(image.shape, np.uint8)
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output_band_stop = np.zeros(image.shape, np.uint8)
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# 边界
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low_pass_threshold = 100
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high_pass_threshold = 100
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band_pass_low_threshold = 100
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band_pass_high_threshold = 200
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band_stop_low_threshold = 100
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band_stop_high_threshold = 200
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for i in range(image.shape[0]):
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for j in range(image.shape[1]):
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pixel_value = image[i][j]
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# 低通滤波器
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if pixel_value <= low_pass_threshold:
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output_low_pass[i][j] = pixel_value
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else:
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output_low_pass[i][j] = 0
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# 高通滤波器
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if pixel_value >= high_pass_threshold:
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output_high_pass[i][j] = pixel_value
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else:
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output_high_pass[i][j] = 0
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# 带通滤波器
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if band_pass_low_threshold < pixel_value <= band_pass_high_threshold:
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output_band_pass[i][j] = pixel_value
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else:
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output_band_pass[i][j] = 0
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# 带阻滤波器
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if band_stop_low_threshold < pixel_value <= band_stop_high_threshold:
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output_band_stop[i][j] = 0
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else:
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output_band_stop[i][j] = pixel_value
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combined = np.hstack((output_low_pass, output_high_pass, output_band_pass, output_band_stop))
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# 更新 edge 变量
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edge = Image.fromarray(combined)
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# 创建Toplevel窗口
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try:
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SelectWin.destroy()
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except Exception:
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print("NVM")
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finally:
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SelectWin = Toplevel()
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SelectWin.attributes('-topmost', True)
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SelectWin.geometry("720x300")
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SelectWin.resizable(True, True) # 可缩放
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SelectWin.title("选择性滤波结果")
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# 显示图像
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LabelPic = tk.Label(SelectWin, text="IMG", width=360, height=240)
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image = ImageTk.PhotoImage(Image.fromarray(combined))
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LabelPic.image = image
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LabelPic['image'] = image
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LabelPic.bind('<Configure>', lambda event: changeSize(event, combined, LabelPic))
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LabelPic.pack(fill=tk.BOTH, expand=tk.YES)
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# 添加保存按钮
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btn_save = tk.Button(SelectWin, text="保存", bg='#add8e6', fg='black', font=('Helvetica', 14), width=20,
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command=savefile)
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btn_save.pack(pady=10)
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return
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