pos97em56
/
Image_Process
1
0
Fork 1
Code Issues Pull Requests Packages Projects Releases Wiki Activity

ADD file via upload

Browse Source
main
pos97em56 5 months ago
parent 4f9d56b57b
commit 49fb1b027c
1 changed files with 319 additions and 0 deletions
Show Stats Download Patch File Download Diff File

319
basic/image_split.py
Unescape View File

@ -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('<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(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('<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(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('<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(LineWin, text="保存", bg='#add8e6', fg='black', font=('Helvetica', 14), width=20,
command=savefile)
btn_save.pack(pady=10)
return
Write Preview
Loading…
Cancel
Save