2024.6.7
所学时间：3小时
代码行数：178
博客园数：1篇
所学知识：今天学习了python的可视化，学会了在开发的过程中，使用的python开发技术。首先使用了这五种库：
1.cv2：这是一个强大的图像处理库，它提供了处理图像的各种功能，包括加载、编辑和保存图像，以及实现各种图像处理算法，如滤波、边缘检测。
2.numpy：用于处理数组和矩阵数据。在图像处理中，它经常被用来进行图像数据的数学运算和转换，例如将图像转换为数组进行处理。
3.PIL：这是 Python 中用于图像处理的标准库，提供了创建、打开、编辑和保存图像的功能。
4.tkinter：用于创建用户界面。它提供了创建各种 GUI 组件的功能，如按钮、标签、文本框等，以及响应用户操作的功能。
5.filedialog：这是 tkinter 库中的一个模块，用于创建文件对话框，让用户选择文件。它用于让用户选择要进行美颜处理的照片文件。
以下是大作业的功能：
1.导入照片：
用户可以从本地文件系统中选择并导入需要进行美颜修图的照片。
2.选择修图功能：
用户可以选择多种美颜修图功能，如磨皮、美白、瘦脸、大眼等。
3.预览修图效果：
用户可以实时预览每种修图功能的效果。
4.保存修图结果：
用户可以将修图后的照片保存到本地文件系统，以便后续查看或分享。
import cv2
import numpy as np
from PIL import Image, ImageTk
import tkinter as tk
from tkinter import filedialog
def convert_to_cartoon(image_path):
# 读取图像
image = cv2.imread(image_path)
# 将图像转换为卡通效果
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
gray = cv2.medianBlur(gray, 5)
edges = cv2.adaptiveThreshold(gray, 255, cv2.ADAPTIVE_THRESH_MEAN_C, cv2.THRESH_BINARY, 9, 9)
color = cv2.bilateralFilter(image, 9, 300, 300)
cartoon = cv2.bitwise_and(color, color, mask=edges)
return cartoon
def beautify(image_path):
# 读取图像
image = cv2.imread(image_path)
# 美颜处理
beauty_image = cv2.GaussianBlur(image, (0, 0), 25)
beauty_image = cv2.addWeighted(image, 1.5, beauty_image, -0.5, 0)
# 大眼效果
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
gray = cv2.medianBlur(gray, 5)
# 检测眼睛区域
eyes = cv2.CascadeClassifier(cv2.data.haarcascades + 'haarcascade_eye.xml')
eyes_rects = eyes.detectMultiScale(gray, scaleFactor=1.3, minNeighbors=5)
# 对每个检测到的眼睛区域进行处理
for (x, y, w, h) in eyes_rects:
eye_center = (x + w // 2, y + h // 2)
radius = int(np.sqrt((w + 6 + h + 2)) / 2)
cv2.circle(beauty_image, eye_center, radius, (0, 0, 0), -1)
return beauty_image
def cartoonize(image_path):
# 读取图像
image = cv2.imread(image_path)
# 将图像转换为卡通效果
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
gray = cv2.medianBlur(gray, 5)
edges = cv2.adaptiveThreshold(gray, 255, cv2.ADAPTIVE_THRESH_MEAN_C, cv2.THRESH_BINARY, 9, 9)
color = cv2.bilateralFilter(image, 9, 300, 300)
cartoon = cv2.bitwise_and(color, color, mask=edges)
return cartoon
def process(image_path):
# 读取图像
img = cv2.imread(image_path)
light=50
# 处理图像
h, w = img.shape[:2]
output = np.zeros((h, w, 3), np.uint8)
for i in range(0, h):
for j in range(0, w):
b, g, r = img[i, j]
x = int(b) + light
y = int(g) + light
z = int(r) + light
if x > 255:
x = 255
if y > 255:
y = 255
if z > 255:
z = 255
output[i, j] = x, y, z
output_rgb = cv2.cvtColor(output, cv2.COLOR_BGR2RGB)
return output_rgb
def convertt(image_path):
img = cv2.imread(image_path)
# 处理图像
gray_img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) # 将图像转换为灰度图像
return gray_img
def smmo(image_path):
# 读取图像
image = cv2.imread(image_path)
# 处理图像
blurred = cv2.GaussianBlur(image, (0, 0), 1) # 对图像进行高斯模糊处理
return blurred
def open_file():
file_path = filedialog.askopenfilename()
if file_path:
image = Image.open(file_path)
image.thumbnail((400, 400))
photo = ImageTk.PhotoImage(image)
panel.config(image=photo)
panel.image = photo
def beautify_image():
global processed_image
processed_image = beautify(file_path)
show_processed_image()
def save_image():
global processed_image
if processed_image is not None:
save_path = filedialog.asksaveasfilename(defaultextension=".jpg")
if save_path:
cv2.imwrite(save_path, processed_image)
def cartoonize_image():
global processed_image
processed_image = cartoonize(file_path)
show_processed_image()
def process_image():
global processed_image, file_path
if file_path:
processed_image = process(file_path)
show_processed_image2()
def convertt_image():
global processed_image, file_path
if file_path:
processed_image = convertt(file_path)
show_processed_image()
def smoo_image():
global processed_image, file_path
if file_path:
processed_image = smmo(file_path)
show_processed_image()
def show_processed_image():
global processed_image
if processed_image is not None:
processed_image_rgb = cv2.cvtColor(processed_image, cv2.COLOR_BGR2RGB)
processed_image_pil = Image.fromarray(processed_image_rgb)
processed_image_pil.thumbnail((400, 400))
photo = ImageTk.PhotoImage(processed_image_pil)
panel.config(image=photo)
panel.image = photo
def show_processed_image2():
global processed_image
# Check if processed image exists
if processed_image is not None:
processed_image_pil = Image.fromarray(processed_image)
processed_image_pil.thumbnail((400, 400))
photo = ImageTk.PhotoImage(processed_image_pil)
panel.config(image=photo)
panel.image = photo
file_path = "Py\myself.jpg"
processed_image = None
root = tk.Tk()
root.title("Image Editor")
# 创建按钮
open_button = tk.Button(root, text="Open Image", command=open_file)
open_button.pack()
beautify_button = tk.Button(root, text="大眼", command=beautify_image)
beautify_button.pack()
cartoonize_button = tk.Button(root, text="卡通", command=cartoonize_image)
cartoonize_button.pack()
process_button=tk.Button(root,text="美白",command=process_image)
process_button.pack()
convertt_button=tk.Button(root,text="滤镜",command=convertt_image)
convertt_button.pack()
smoo_button=tk.Button(root,text="磨皮",command=smoo_image)
smoo_button.pack()
save_button = tk.Button(root, text="保存", command=save_image)
save_button.pack()
# 显示图片的面板
panel = tk.Label(root)
panel.pack()
root.mainloop()
