Delete 'basic/image_sharp.py'

5 months ago · 7a94dd9bfa
parent 393a399eeb
commit 7a94dd9bfa
1 changed files with 0 additions and 372 deletions
--- a/basic/image_sharp.py
+++ b/basic/image_sharp.py
@ -1,372 +0,0 @@
-import tkinter as tk
-from tkinter import filedialog, messagebox
-from tkinter import Toplevel
-from PIL import Image, ImageTk
-import numpy as np
-import cv2
-import os
-
-img_path = ""  # 全局变量，用于存储图像路径
-src = None  # 全局变量，用于存储已选择的图像
-img_label = None  # 全局变量，用于存储显示选择的图片的标签
-edge = None
-
-FreqsharWin = 0
-AirsharWin = 0
-
-def select_image(root):
-    global img_path, src, img_label, edge
-
-    img_path = filedialog.askopenfilename(filetypes=[("Image files", "*.jpg;*.png;*.jpeg;*.bmp")])
-    if img_path:
-        # 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
-        img_path_fixed = os.path.normpath(img_path)
-
-        # 图像输入
-        src_temp = cv2.imdecode(np.fromfile(img_path_fixed, dtype=np.uint8), cv2.IMREAD_UNCHANGED)
-        if src_temp is None:
-            messagebox.showerror("错误", "无法读取图片，请选择有效的图片路径")
-            return
-        src = cv2.cvtColor(src_temp, cv2.COLOR_BGR2RGB)
-
-        # 检查 img_label 是否存在且有效
-        if img_label is None or not img_label.winfo_exists():
-            img_label = tk.Label(root)
-            img_label.pack(side=tk.TOP, pady=10)
-
-        img = Image.open(img_path)
-        img.thumbnail((160, 160))
-        img_tk = ImageTk.PhotoImage(img)
-        img_label.configure(image=img_tk)
-        img_label.image = img_tk
-
-        # 定义 edge 变量为 PIL.Image 对象，以便稍后保存
-        edge = Image.fromarray(src)
-    else:
-        messagebox.showerror("错误", "没有选择图片路径")
-
-def select_image(root):
-    global img_path, src, img_label
-
-    img_path = filedialog.askopenfilename(filetypes=[("Image files", "*.jpg;*.png;*.jpeg;*.bmp")])
-    if img_path:
-        # 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
-        img_path_fixed = os.path.normpath(img_path)
-
-        # 图像输入
-        src_temp = cv2.imdecode(np.fromfile(img_path_fixed, dtype=np.uint8), cv2.IMREAD_UNCHANGED)
-        if src_temp is None:
-            messagebox.showerror("错误", "无法读取图片，请选择有效的图片路径")
-            return
-        src = cv2.cvtColor(src_temp, cv2.COLOR_BGR2RGB)
-
-        # 检查 img_label 是否存在且有效
-        if img_label is None or not img_label.winfo_exists():
-            img_label = tk.Label(root)
-            img_label.pack(side=tk.TOP, pady=10)
-
-        img = Image.open(img_path)
-        img.thumbnail((160, 160))
-        img_tk = ImageTk.PhotoImage(img)
-        img_label.configure(image=img_tk)
-        img_label.image = img_tk
-        src = cv2.cvtColor(src, cv2.COLOR_BGR2RGB)
-    else:
-        messagebox.showerror("错误", "没有选择图片路径")
-
-def show_selected_image(root):
-    global img_label
-    img_label = tk.Label(root)
-    img_label.pack(side=tk.TOP, pady=10)
-    img = Image.open(img_path)
-    img.thumbnail((200, 200))
-    img_tk = ImageTk.PhotoImage(img)
-    img_label.configure(image=img_tk)
-    img_label.image = img_tk
-
-def changeSize(event, img, LabelPic):
-    img_aspect = img.shape[1] / img.shape[0]
-    new_aspect = event.width / event.height
-
-    if new_aspect > img_aspect:
-        new_width = int(event.height * img_aspect)
-        new_height = event.height
-    else:
-        new_width = event.width
-        new_height = int(event.width / img_aspect)
-
-    resized_image = cv2.resize(img, (new_width, new_height))
-    image1 = ImageTk.PhotoImage(Image.fromarray(resized_image))
-    LabelPic.image = image1
-    LabelPic['image'] = image1
-
-def savefile():
-    global edge
-
-    filename = filedialog.asksaveasfilename(defaultextension=".jpg", filetypes=[("JPEG files", "*.jpg"), ("PNG files", "*.png"), ("BMP files", "*.bmp")])
-    if not filename:
-        return
-    # 确保 edge 变量已定义
-    if edge is not None:
-        try:
-            edge.save(filename)
-            messagebox.showinfo("保存成功", "图片保存成功！")
-        except Exception as e:
-            messagebox.showerror("保存失败", f"无法保存图片: {e}")
-    else:
-        messagebox.showerror("保存失败", "没有图像可保存")
-
-#频域锐化
-def freq_shar(root):
-    global src, FreqsharWin, edge
-
-    # 判断是否已经选取图片
-    if src is None:
-        messagebox.showerror("错误", "没有选择图片！")
-        return
-
-    def Ideal_HighPassFilter(rows, cols, crow, ccol, D0=40):
-        # 创建空白图像以存储滤波结果
-        Ideal_HighPass = np.zeros((rows, cols), np.uint8)
-
-        # 计算理想高通滤波器
-        for i in range(rows):
-            for j in range(cols):
-                D = np.sqrt((i - crow) ** 2 + (j - ccol) ** 2)
-                if D >= D0:
-                    Ideal_HighPass[i, j] = 255
-
-        # 应用滤波器到频域表示
-        mask = Ideal_HighPass[:, :, np.newaxis]
-        fshift = dft_shift * mask
-
-        # 逆傅里叶变换以获得处理后的图像
-        f_ishift = np.fft.ifftshift(fshift)
-        img_back = cv2.idft(f_ishift)
-        img_back = cv2.magnitude(img_back[:, :, 0], img_back[:, :, 1])
-
-        # 归一化图像到0-255
-        cv2.normalize(img_back, img_back, 0, 255, cv2.NORM_MINMAX)
-        img_back = np.uint8(img_back)
-
-        return img_back
-
-    def ButterWorth_HighPassFilter(rows, cols, crow, ccol, D0=40, n=2):
-        # 创建空白图像以存储滤波结果
-        ButterWorth_HighPass = np.zeros((rows, cols), np.uint8)
-
-        # 计算 Butterworth 高通滤波器
-        for i in range(rows):
-            for j in range(cols):
-                D = np.sqrt((i - crow) ** 2 + (j - ccol) ** 2)
-                if D == 0:
-                    ButterWorth_HighPass[i, j] = 0  # 如果 D = 0，直接赋值为 0，避免除以零错误
-                else:
-                    ButterWorth_HighPass[i, j] = 255 / (1 + (D0 / D) ** (2 * n))
-
-        # 应用滤波器到频域表示
-        mask = ButterWorth_HighPass[:, :, np.newaxis]
-        fshift = dft_shift * mask
-
-        # 逆傅里叶变换以获得处理后的图像
-        f_ishift = np.fft.ifftshift(fshift)
-        img_back = cv2.idft(f_ishift)
-        img_back = cv2.magnitude(img_back[:, :, 0], img_back[:, :, 1])
-
-        # 归一化图像到0-255
-        cv2.normalize(img_back, img_back, 0, 255, cv2.NORM_MINMAX)
-        img_back = np.uint8(img_back)
-
-        return img_back
-
-    def Gauss_HighPassFilter(rows, cols, crow, ccol, D0=40):
-        # 创建空白图像以存储滤波结果
-        Gauss_HighPass = np.zeros((rows, cols), np.uint8)
-
-        # 计算 Gauss 高通滤波器
-        for i in range(rows):
-            for j in range(cols):
-                D = np.sqrt((i - crow) ** 2 + (j - ccol) ** 2)
-                Gauss_HighPass[i, j] = 255 * (1 - np.exp(-0.5 * (D ** 2) / (D0 ** 2)))
-
-        # 应用滤波器到频域表示
-        mask = Gauss_HighPass[:, :, np.newaxis]
-        fshift = dft_shift * mask
-
-        # 逆傅里叶变换以获得平滑后的图像
-        f_ishift = np.fft.ifftshift(fshift)
-        img_back = cv2.idft(f_ishift)
-        img_back = cv2.magnitude(img_back[:, :, 0], img_back[:, :, 1])
-
-        # 归一化图像到0-255
-        cv2.normalize(img_back, img_back, 0, 255, cv2.NORM_MINMAX)
-        img_back = np.uint8(img_back)
-
-        return img_back
-
-    # 读取灰度图像
-    im = cv2.cvtColor(src, cv2.COLOR_BGR2GRAY)
-
-    # 获取图像尺寸
-    rows, cols = im.shape
-    crow, ccol = rows // 2, cols // 2  # 中心位置
-
-    # 获取图像的频域表示
-    dft = cv2.dft(np.float32(im), flags=cv2.DFT_COMPLEX_OUTPUT)
-    dft_shift = np.fft.fftshift(dft)
-
-    # 理想高通滤波器
-    Ideal_HighPass = Ideal_HighPassFilter(rows, cols, crow, ccol)
-    # 巴特沃斯高通滤波器
-    ButterWorth_HighPass = ButterWorth_HighPassFilter(rows, cols, crow, ccol)
-    # 高斯高通滤波器
-    Gauss_HighPass = Gauss_HighPassFilter(rows, cols, crow, ccol)
-
-    combined = np.hstack((Ideal_HighPass, ButterWorth_HighPass, Gauss_HighPass))
-
-    # 更新 edge 变量
-    edge = Image.fromarray(combined)
-
-    # 创建Toplevel窗口
-    try:
-        FreqsharWin.destroy()
-    except Exception as e:
-        print("NVM")
-    finally:
-        FreqsharWin = Toplevel()
-        FreqsharWin.attributes('-topmost', True)
-    FreqsharWin.geometry("720x300")
-    FreqsharWin.resizable(True, True)  # 可缩放
-    FreqsharWin.title("频域锐化结果")
-
-    # 显示图像
-    LabelPic = tk.Label(FreqsharWin, text="IMG", width=720, height=240)
-    image = ImageTk.PhotoImage(Image.fromarray(combined))
-    LabelPic.image = image
-    LabelPic['image'] = image
-
-    LabelPic.bind('<Configure>', lambda event: changeSize(event, combined, LabelPic))
-    LabelPic.pack(fill=tk.BOTH, expand=tk.YES)
-
-    # 添加保存按钮
-    btn_save = tk.Button(FreqsharWin, text="保存", bg='#add8e6', fg='black', font=('Helvetica', 14), width=20,
-                         command=savefile)
-    btn_save.pack(pady=10)
-
-    return
-
-#空域锐化
-def air_shar(root):
-    global src, AirsharWin, edge
-
-    # 判断是否已经选取图片
-    if src is None:
-        messagebox.showerror("错误", "没有选择图片！")
-        return
-
-    def Roberts(Image_In, height, width):
-        # 创建输出图像
-        Roberts = np.zeros((height - 1, width - 1), dtype=np.uint8)
-
-        # 进行Roberts边缘检测
-        for i in range(height - 1):
-            for j in range(width - 1):
-                tmp = abs(int(Image_In[i + 1, j + 1]) - int(Image_In[i, j])) + abs(
-                    int(Image_In[i + 1, j]) - int(Image_In[i, j + 1]))
-                tmp = max(0, min(255, tmp))  # 确保结果在0到255之间
-                Roberts[i, j] = tmp
-
-        return Roberts
-
-    def Sobel(Image_In, height, width):
-        # 创建输出图像
-        Image_Sobel = np.zeros((height - 2, width - 2), dtype=np.uint8)
-
-        # 进行Sobel边缘检测
-        for i in range(1, height - 1):
-            for j in range(1, width - 1):
-                # 使用Sobel算子计算水平和垂直方向的梯度
-                tmp1 = abs(-int(Image_In[i - 1, j - 1]) - 2 * int(Image_In[i - 1, j]) - int(Image_In[i - 1, j + 1]) +
-                           int(Image_In[i + 1, j - 1]) + 2 * int(Image_In[i + 1, j]) + int(Image_In[i + 1, j + 1]))
-                tmp2 = abs(-int(Image_In[i - 1, j - 1]) - 2 * int(Image_In[i, j - 1]) - int(Image_In[i + 1, j - 1]) +
-                           int(Image_In[i - 1, j + 1]) + 2 * int(Image_In[i, j + 1]) + int(Image_In[i + 1, j + 1]))
-                tmp = tmp1 + tmp2
-                tmp = max(0, min(255, tmp))  # 确保结果在0到255之间
-                Image_Sobel[i - 1, j - 1] = tmp
-
-        return Image_Sobel
-
-    def Prewitt(Image_In, height, width):
-        # 创建输出图像
-        Image_Prewitt = np.zeros((height - 2, width - 2), dtype=np.uint8)
-
-        # 进行Prewitt边缘检测
-        for i in range(1, height - 1):
-            for j in range(1, width - 1):
-                # 使用Prewitt算子计算水平和垂直方向的梯度
-                tmp1 = abs(-int(Image_In[i - 1, j - 1]) - int(Image_In[i - 1, j]) - int(Image_In[i - 1, j + 1]) +
-                           int(Image_In[i + 1, j - 1]) + int(Image_In[i + 1, j]) + int(Image_In[i + 1, j + 1]))
-                tmp2 = abs(-int(Image_In[i - 1, j - 1]) - int(Image_In[i, j - 1]) - int(Image_In[i + 1, j - 1]) +
-                           int(Image_In[i - 1, j + 1]) + int(Image_In[i, j + 1]) + int(Image_In[i + 1, j + 1]))
-                tmp = tmp1 + tmp2
-                tmp = max(0, min(255, tmp))  # 确保结果在0到255之间
-                Image_Prewitt[i - 1, j - 1] = tmp
-
-        return Image_Prewitt
-
-    im = cv2.cvtColor(src, cv2.COLOR_BGR2GRAY)
-
-    # 获取图像的尺寸
-    height, width = im.shape
-
-    # Roberts
-    Rob = Roberts(im, height, width)
-    # Sobel
-    Sob = Sobel(im, height, width)
-    # Prewitt
-    Pre = Prewitt(im, height, width)
-    # # Laplacian
-    # Lap = Laplacian(im, height, width)
-
-    # 找出最小的尺寸
-    min_height = min(Rob.shape[0], Sob.shape[0], Pre.shape[0])
-    min_width = min(Rob.shape[1], Sob.shape[1], Pre.shape[1])
-
-    # 对所有结果进行裁剪，使它们的尺寸一致
-    Rob = Rob[:min_height, :min_width]
-    Sob = Sob[:min_height, :min_width]
-    Pre = Pre[:min_height, :min_width]
-    # Lap = Lap[:min_height, :min_width]
-
-    combined = np.hstack((Rob, Sob, Pre))
-
-    # 更新 edge 变量
-    edge = Image.fromarray(combined)
-
-    # 创建Toplevel窗口
-    try:
-        AirsharWin.destroy()
-    except Exception as e:
-        print("NVM")
-    finally:
-        AirsharWin = Toplevel()
-        AirsharWin.attributes('-topmost', True)
-    AirsharWin.geometry("720x300")
-    AirsharWin.resizable(True, True)  # 可缩放
-    AirsharWin.title("空域锐化结果")
-
-    # 显示图像
-    LabelPic = tk.Label(AirsharWin, text="IMG", width=720, height=240)
-    image = ImageTk.PhotoImage(Image.fromarray(combined))
-    LabelPic.image = image
-    LabelPic['image'] = image
-
-    LabelPic.bind('<Configure>', lambda event: changeSize(event, combined, LabelPic))
-    LabelPic.pack(fill=tk.BOTH, expand=tk.YES)
-
-    # 添加保存按钮
-    btn_save = tk.Button(AirsharWin, text="保存", bg='#add8e6', fg='black', font=('Helvetica', 14), width=20,
-                         command=savefile)
-    btn_save.pack(pady=10)
-
-    return