From 49fb1b027c5d540144a385fdad0524aebd83d2cd Mon Sep 17 00:00:00 2001 From: pos97em56 <10225101485@ecnu.stu.edu.cn> Date: Tue, 2 Jul 2024 22:58:03 +0800 Subject: [PATCH] ADD file via upload --- basic/image_split.py | 319 +++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 319 insertions(+) create mode 100644 basic/image_split.py diff --git a/basic/image_split.py b/basic/image_split.py new file mode 100644 index 0000000..c6fa73a --- /dev/null +++ b/basic/image_split.py @@ -0,0 +1,319 @@ +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