diff --git a/basic/image_split.py b/basic/image_split.py deleted file mode 100644 index c6fa73a..0000000 --- a/basic/image_split.py +++ /dev/null @@ -1,319 +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 -X = None # 用于存储第一张图像 -Y = None # 用于存储第二张图像 -img_label = None # 全局变量，用于存储显示选择的图片的标签 -edge = None - -ThreWin = None -VergeWin = None -LineWin = None - -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 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((160, 160)) - 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") - -#阈值化 -def threshold(root): - global src, ThreWin, 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 - - # 转变图像为灰度图 - gray = cv2.cvtColor(src, cv2.COLOR_BGR2GRAY) - - #TRIANGLE自适应阈值 - ret, TRIANGLE_img = cv2.threshold(gray, 0, 255, cv2.THRESH_TRIANGLE) - - #OTSU自适应阈值 - ret, OTSU_img = cv2.threshold(gray, 0, 255, cv2.THRESH_OTSU) - - #TRUNC截断阈值(200) - ret, TRUNC_img = cv2.threshold(gray, 200, 255, cv2.THRESH_TRUNC) - - #TOZERO归零阈值(100) - ret, TOZERO__img = cv2.threshold(gray, 100, 255, cv2.THRESH_TOZERO) - - combined = np.hstack((TRIANGLE_img, OTSU_img, TRUNC_img, TOZERO__img)) - # 更新 edge 变量 - edge = Image.fromarray(combined) - - # 创建Toplevel窗口 - try: - ThreWin.destroy() - except Exception as e: - print("NVM") - finally: - ThreWin = Toplevel() - ThreWin.attributes('-topmost', True) - ThreWin.geometry("720x300") - ThreWin.resizable(True, True) # 可缩放 - ThreWin.title("阈值化结果") - - # 显示图像 - LabelPic = tk.Label(ThreWin, text="IMG", width=720, height=240) - image = ImageTk.PhotoImage(Image.fromarray(combined)) - LabelPic.image = image - LabelPic['image'] = image - - LabelPic.bind('', lambda event: changeSize(event, combined, LabelPic)) - LabelPic.pack(fill=tk.BOTH, expand=tk.YES) - - # 添加保存按钮 - btn_save = tk.Button(ThreWin, text="保存", bg='#add8e6', fg='black', font=('Helvetica', 14), width=20, - command=savefile) - btn_save.pack(pady=10) - - return - -#边缘检测 -def verge(root): - global src, VergeWin, 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 - - # 转变图像为灰度图 - grayImage = cv2.cvtColor(src, cv2.COLOR_BGR2GRAY) - - #1.Roberts算子 - kernelx = np.array([[-1, 0], [0, 1]], dtype=int) - kernely = np.array([[0, -1], [1, 0]], dtype=int) - #卷积操作 - x = cv2.filter2D(grayImage, cv2.CV_16S, kernelx) - y = cv2.filter2D(grayImage, cv2.CV_16S, kernely) - #数据格式转换 - absX = cv2.convertScaleAbs(x) - absY = cv2.convertScaleAbs(y) - Roberts = cv2.addWeighted(absX, 0.5, absY, 0.5, 0) - - #2.Sobel算子 - x = cv2.Sobel(grayImage, cv2.CV_16S, 1, 0) - y = cv2.Sobel(grayImage, cv2.CV_16S, 0, 1) - #数据格式转换 - absX = cv2.convertScaleAbs(x) - absY = cv2.convertScaleAbs(y) - #组合图像 - Sobel = cv2.addWeighted(absX, 0.5, absY, 0.5, 0) - - #3.拉普拉斯算法&高斯滤波 - gray = cv2.GaussianBlur(grayImage, (5, 5), 0, 0) - dst = cv2.Laplacian(gray, cv2.CV_16S, ksize=3) - #数据格式转换 - Laplacian = cv2.convertScaleAbs(dst) - - #4.LoG边缘算子&边缘扩充&高斯滤波 - gray = cv2.copyMakeBorder(grayImage, 2, 2, 2, 2, borderType=cv2.BORDER_REPLICATE) - image = cv2.GaussianBlur(gray, (3, 3), 0, 0) - #使用Numpy定义LoG算子 - m1 = np.array( - [[0, 0, -1, 0, 0], [0, -1, -2, -1, 0], [-1, -2, 16, -2, -1], [0, -1, -2, -1, 0], [0, 0, -1, 0, 0]]) - #卷积运算 - rows = image.shape[0] - cols = image.shape[1] - image1 = np.zeros(image.shape) - # 为了使卷积对每个像素都进行运算，原图像的边缘像素要对准模板的中心。 - # 由于图像边缘扩大了2像素，因此要从位置2到行(列)-2 - for i in range(2, rows - 2): - for j in range(2, cols - 2): - image1[i, j] = np.sum((m1 * image[i - 2:i + 3, j - 2:j + 3])) - - #数据格式转换 - Log = cv2.convertScaleAbs(image1) - - #5.Sobel算子 - image = cv2.GaussianBlur(grayImage, (3, 3), 0) - #求x，y方向的Sobel算子 - gradx = cv2.Sobel(image, cv2.CV_16SC1, 1, 0) - grady = cv2.Sobel(image, cv2.CV_16SC1, 0, 1) - #使用Canny函数处理图像，x,y分别是3求出来的梯度，低阈值50，高阈值150 - edge_output = cv2.Canny(gradx, grady, 50, 150) - - Roberts = cv2.resize(Roberts, (grayImage.shape[1], grayImage.shape[0])) - Sobel = cv2.resize(Sobel, (grayImage.shape[1], grayImage.shape[0])) - Laplacian = cv2.resize(Laplacian, (grayImage.shape[1], grayImage.shape[0])) - Log = cv2.resize(Log, (grayImage.shape[1], grayImage.shape[0])) - edge_output = cv2.resize(edge_output, (grayImage.shape[1], grayImage.shape[0])) - - combined = np.hstack((Roberts, Sobel, Laplacian, Log, edge_output)) - - # 更新 edge 变量 - edge = Image.fromarray(combined) - - # 创建Toplevel窗口 - try: - VergeWin.destroy() - except Exception as e: - print("NVM") - finally: - VergeWin = Toplevel() - VergeWin.attributes('-topmost', True) - VergeWin.geometry("720x300") - VergeWin.resizable(True, True) # 可缩放 - VergeWin.title("边缘检测结果") - - # 显示图像 - LabelPic = tk.Label(VergeWin, text="IMG", width=720, height=240) - image = ImageTk.PhotoImage(Image.fromarray(combined)) - LabelPic.image = image - LabelPic['image'] = image - - LabelPic.bind('', lambda event: changeSize(event, combined, LabelPic)) - LabelPic.pack(fill=tk.BOTH, expand=tk.YES) - - # 添加保存按钮 - btn_save = tk.Button(VergeWin, text="保存", bg='#add8e6', fg='black', font=('Helvetica', 14), width=20, - command=savefile) - btn_save.pack(pady=10) - return - -#线条变化检测 -def line_chan(root): - global src, LineWin, 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 - - img = cv2.GaussianBlur(src, (3, 3), 0) - edges = cv2.Canny(img, 50, 150, apertureSize=3) - - # 使用HoughLines算法 - lines = cv2.HoughLines(edges, 1, np.pi / 2, 118) - result = img.copy() - for i_line in lines: - for line in i_line: - rho = line[0] - theta = line[1] - if (theta < (np.pi / 4.)) or (theta > (3. * np.pi / 4.0)): # 垂直直线 - pt1 = (int(rho / np.cos(theta)), 0) - pt2 = (int((rho - result.shape[0] * np.sin(theta)) / np.cos(theta)), result.shape[0]) - cv2.line(result, pt1, pt2, (0, 0, 255)) - else: - pt1 = (0, int(rho / np.sin(theta))) - pt2 = (result.shape[1], int((rho - result.shape[1] * np.cos(theta)) / np.sin(theta))) - cv2.line(result, pt1, pt2, (0, 0, 255), 1) - - # 使用HoughLinesP算法 - minLineLength = 200 - maxLineGap = 15 - linesP = cv2.HoughLinesP(edges, 1, np.pi / 180, 80, minLineLength, maxLineGap) - result_P = img.copy() - for i_P in linesP: - for x1, y1, x2, y2 in i_P: - cv2.line(result_P, (x1, y1), (x2, y2), (0, 255, 0), 3) - - combined = np.hstack((result, result_P)) - combined = cv2.cvtColor(combined, cv2.COLOR_BGR2RGB) - # 更新 edge 变量 - edge = Image.fromarray(result) - - # 创建Toplevel窗口 - try: - LineWin.destroy() - except Exception as e: - print("NVM") - finally: - LineWin = Toplevel() - LineWin.attributes('-topmost', True) - LineWin.geometry("720x300") - LineWin.resizable(True, True) # 可缩放 - LineWin.title("线条变化检测结果") - - # 显示图像 - LabelPic = tk.Label(LineWin, text="IMG", width=720, height=240) - image = ImageTk.PhotoImage(Image.fromarray(cv2.cvtColor(combined, cv2.COLOR_BGR2RGB))) - LabelPic.image = image - LabelPic['image'] = image - - LabelPic.bind('', lambda event: changeSize(event, combined, LabelPic)) - LabelPic.pack(fill=tk.BOTH, expand=tk.YES) - - # 添加保存按钮 - btn_save = tk.Button(LineWin, text="保存", bg='#add8e6', fg='black', font=('Helvetica', 14), width=20, - command=savefile) - btn_save.pack(pady=10) - return \ No newline at end of file