Initial commit

.idea/.gitignore

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+# 默认忽略的文件
+/shelf/
+/workspace.xml
+# 基于编辑器的 HTTP 客户端请求
+/httpRequests/
+# Datasource local storage ignored files
+/dataSources/
+/dataSources.local.xml

.idea/djangoProject.iml

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+<?xml version="1.0" encoding="UTF-8"?>
+<module type="PYTHON_MODULE" version="4">
+  <component name="FacetManager">
+    <facet type="django" name="Django">
+      <configuration>
+        <option name="rootFolder" value="$MODULE_DIR$" />
+        <option name="settingsModule" value="djangoProject/settings.py" />
+        <option name="manageScript" value="$MODULE_DIR$/manage.py" />
+        <option name="environment" value="&lt;map/&gt;" />
+        <option name="doNotUseTestRunner" value="false" />
+        <option name="trackFilePattern" value="migrations" />
+      </configuration>
+    </facet>
+  </component>
+  <component name="NewModuleRootManager">
+    <content url="file://$MODULE_DIR$">
+      <excludeFolder url="file://$MODULE_DIR$/venv" />
+    </content>
+    <orderEntry type="inheritedJdk" />
+    <orderEntry type="sourceFolder" forTests="false" />
+    <orderEntry type="library" name="@types/jquery" level="application" />
+    <orderEntry type="library" name="jquery" level="application" />
+  </component>
+  <component name="TemplatesService">
+    <option name="TEMPLATE_CONFIGURATION" value="Django" />
+    <option name="TEMPLATE_FOLDERS">
+      <list>
+        <option value="$MODULE_DIR$/../djangoProject\templates" />
+      </list>
+    </option>
+  </component>
+</module>

.idea/inspectionProfiles/profiles_settings.xml

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+<component name="InspectionProjectProfileManager">
+  <settings>
+    <option name="USE_PROJECT_PROFILE" value="false" />
+    <version value="1.0" />
+  </settings>
+</component>

.idea/jsLibraryMappings.xml

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+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="JavaScriptLibraryMappings">
+    <file url="file://$PROJECT_DIR$" libraries="{jquery}" />
+    <file url="PROJECT" libraries="{@types/jquery}" />
+  </component>
+</project>

.idea/misc.xml

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+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="ProjectRootManager" version="2" project-jdk-name="Python 3.10 (djangoProject)" project-jdk-type="Python SDK" />
+</project>

.idea/modules.xml

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+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="ProjectModuleManager">
+    <modules>
+      <module fileurl="file://$PROJECT_DIR$/.idea/djangoProject.iml" filepath="$PROJECT_DIR$/.idea/djangoProject.iml" />
+    </modules>
+  </component>
+</project>

djangoProject/asgi.py

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+"""
+ASGI config for djangoProject project.
+
+It exposes the ASGI callable as a module-level variable named ``application``.
+
+For more information on this file, see
+https://docs.djangoproject.com/en/4.0/howto/deployment/asgi/
+"""
+
+import os
+
+from django.core.asgi import get_asgi_application
+
+os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'djangoProject.settings')
+
+application = get_asgi_application()

djangoProject/settings.py

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+"""
+Django settings for djangoProject project.
+
+Generated by 'django-admin startproject' using Django 4.0.6.
+
+For more information on this file, see
+https://docs.djangoproject.com/en/4.0/topics/settings/
+
+For the full list of settings and their values, see
+https://docs.djangoproject.com/en/4.0/ref/settings/
+"""
+import os
+from pathlib import Path
+
+# Build paths inside the project like this: BASE_DIR / 'subdir'.
+BASE_DIR = Path(__file__).resolve().parent.parent
+
+
+# Quick-start development settings - unsuitable for production
+# See https://docs.djangoproject.com/en/4.0/howto/deployment/checklist/
+
+# SECURITY WARNING: keep the secret key used in production secret!
+SECRET_KEY = 'django-insecure-ya9!!nl84l$a#)ez8np*9k4=y0vq8qv+dm)f+pub3x48^e7am&'
+
+# SECURITY WARNING: don't run with debug turned on in production!
+DEBUG = True
+
+ALLOWED_HOSTS = []
+
+
+# Application definition
+
+INSTALLED_APPS = [
+    'django.contrib.admin',
+    'django.contrib.auth',
+    'django.contrib.contenttypes',
+    'django.contrib.sessions',
+    'django.contrib.messages',
+    'django.contrib.staticfiles',
+]
+
+MIDDLEWARE = [
+    'django.middleware.security.SecurityMiddleware',
+    'django.contrib.sessions.middleware.SessionMiddleware',
+    'django.middleware.common.CommonMiddleware',
+    'django.middleware.csrf.CsrfViewMiddleware',
+    'django.contrib.auth.middleware.AuthenticationMiddleware',
+    'django.contrib.messages.middleware.MessageMiddleware',
+    'django.middleware.clickjacking.XFrameOptionsMiddleware',
+]
+
+ROOT_URLCONF = 'djangoProject.urls'
+
+TEMPLATES = [
+    {
+        'BACKEND': 'django.template.backends.django.DjangoTemplates',
+        'DIRS': [BASE_DIR / 'templates']
+        ,
+        'APP_DIRS': True,
+        'OPTIONS': {
+            'context_processors': [
+                'django.template.context_processors.debug',
+                'django.template.context_processors.request',
+                'django.contrib.auth.context_processors.auth',
+                'django.contrib.messages.context_processors.messages',
+            ],
+        },
+    },
+]
+
+WSGI_APPLICATION = 'djangoProject.wsgi.application'
+
+
+# Database
+# https://docs.djangoproject.com/en/4.0/ref/settings/#databases
+
+DATABASES = {
+    'default': {
+        'ENGINE': 'django.db.backends.sqlite3',
+        'NAME': BASE_DIR / 'db.sqlite3',
+    }
+}
+
+
+# Password validation
+# https://docs.djangoproject.com/en/4.0/ref/settings/#auth-password-validators
+
+AUTH_PASSWORD_VALIDATORS = [
+    {
+        'NAME': 'django.contrib.auth.password_validation.UserAttributeSimilarityValidator',
+    },
+    {
+        'NAME': 'django.contrib.auth.password_validation.MinimumLengthValidator',
+    },
+    {
+        'NAME': 'django.contrib.auth.password_validation.CommonPasswordValidator',
+    },
+    {
+        'NAME': 'django.contrib.auth.password_validation.NumericPasswordValidator',
+    },
+]
+
+
+# Internationalization
+# https://docs.djangoproject.com/en/4.0/topics/i18n/
+
+LANGUAGE_CODE = 'en-us'
+
+TIME_ZONE = 'UTC'
+
+USE_I18N = True
+
+USE_TZ = True
+
+
+# Static files (CSS, JavaScript, Images)
+# https://docs.djangoproject.com/en/4.0/howto/static-files/
+
+STATIC_URL = 'static/'
+
+# Default primary key field type
+# https://docs.djangoproject.com/en/4.0/ref/settings/#default-auto-field
+
+DEFAULT_AUTO_FIELD = 'django.db.models.BigAutoField'
+
+STATICFILES_DIRS = [
+    os.path.join(BASE_DIR, 'static'),
+]
+MEDIA_ROOT = os.path.join(BASE_DIR, 'static/media')

djangoProject/urls.py

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+"""djangoProject URL Configuration
+
+The `urlpatterns` list routes URLs to views. For more information please see:
+    https://docs.djangoproject.com/en/4.0/topics/http/urls/
+Examples:
+Function views
+    1. Add an import:  from my_app import views
+    2. Add a URL to urlpatterns:  path('', views.home, name='home')
+Class-based views
+    1. Add an import:  from other_app.views import Home
+    2. Add a URL to urlpatterns:  path('', Home.as_view(), name='home')
+Including another URLconf
+    1. Import the include() function: from django.urls import include, path
+    2. Add a URL to urlpatterns:  path('blog/', include('blog.urls'))
+"""
+from django.contrib import admin
+from django.urls import path
+from . import views
+
+urlpatterns = [
+    path('', views.to_img_load),
+    path('histogram/', views.histogram),
+    path('greyHistogram/', views.greyHistogram),
+    path('colorHistogram/', views.colorHistogram),
+    path('piecewiseLinearProcessing/', views.piecewiseLinearProcessing),
+    path('enlarge/', views.enlarge),
+    path('move/', views.move),
+    path('spin/', views.spin),
+    path('horizontalFlip/', views.horizontalFlip),
+    path('verticalFlip/', views.verticalFlip),
+    path('crossFlip/', views.crossFlip),
+    path('affineTransformation/', views.affineTransformation),
+    path('enhance/', views.enhance),
+    path('robs/', views.robs),
+    path('sob/', views.sob),
+    path('lap/', views.lap),
+    path('log/', views.log),
+    path('cny/', views.cny),
+    path('MeanFilter/', views.MeanFilter),
+    path('MedFilter/', views.MedFilter),
+    path('HoughLineChange/', views.HoughLineChange),
+    path('erode/', views.erode),
+    path('dialate/', views.dialate),
+    path('sp_noise/', views.sp_noise),
+    path('gasuss_noise/', views.gasuss_noise),
+    path('highPassFilter/', views.highPassFilter),
+    path('IdealLowPassFiltering/', views.IdealLowPassFiltering),
+    path('butterworth_low_filter/', views.butterworth_low_filter),
+    path('IdealHighPassFiltering/', views.IdealHighPassFiltering),
+    path('butterworth_high_filter/', views.butterworth_high_filter),
+    path('sharpen/', views.sharpen)
+]

djangoProject/views.py

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+import base64
+import random
+from tkinter import Image
+import numpy as np
+import cv2
+import sys
+import cv2 as cv
+import matplotlib.pyplot as plt
+import numpy as np
+from PIL import Image
+from django.http import HttpResponse, JsonResponse
+from django.shortcuts import render
+from matplotlib import pyplot as plt
+
+
+from djangoProject import settings
+
+
+# 主页面
+def to_img_load(request):
+    return render(request, 'upload.html')
+
+
+# 绘制直方图
+def histogram(request):
+    if request.method == 'POST':
+        image = request.FILES.get('picture')
+        name = image.name
+        print(name)
+        path = settings.MEDIA_ROOT + '/' + image.name
+        with open(path, 'wb') as pic:
+            for c in image.chunks():
+                pic.write(c)
+        img = cv2.imread(path)
+        color = ('b', 'g', 'r')
+        for i, col in enumerate(color):
+            hist = cv2.calcHist([img], [i], None, [256], [0, 256])
+            plt.plot(hist, color=col)
+            plt.xlim([0, 256])
+        plt.savefig(path)
+        try:
+            data = {'state': 'static/media/'+name}
+        except:
+            data = {'state': 0}
+        return JsonResponse(data)
+
+
+# 灰度直方图
+def greyHistogram(request):
+    if request.method == 'POST':
+        image = request.FILES.get('picture')
+        name = image.name
+        img_path = settings.MEDIA_ROOT + '/' + image.name
+        print(img_path)
+        with open(img_path, 'wb') as pic:
+            for c in image.chunks():
+                pic.write(c)
+        img_PIL = Image.open(img_path)
+        img = np.array(img_PIL)
+        img_gray = cv.cvtColor(img, cv.COLOR_RGB2GRAY)
+        hist = cv.calcHist([img_gray], [0], None, [256], [0, 255])
+        plt.plot(hist)
+        plt.xlim([0, 255])
+        plt.savefig(img_path)
+        try:
+            data = {'state': 'static/media/'+name}
+        except:
+            data = {'state': 0}
+        return JsonResponse(data)
+
+
+# 彩色直方图
+def colorHistogram(request):
+    if request.method == 'POST':
+        color = ["r", "g", "b"]
+        image = request.FILES.get('picture')
+        name = image.name
+        img_path = settings.MEDIA_ROOT + '/' + image.name
+        with open(img_path, 'wb') as pic:
+            for c in image.chunks():
+                pic.write(c)
+        img = cv2.imread(img_path)
+        b, g, r = cv2.split(img)
+        img = cv2.merge([r, g, b])
+        # 绘制彩色直方图，需要对每个通道进行遍历，并且找到最大值和最小值
+        for index, c in enumerate(color):
+            hist = cv2.calcHist([img], [index], None, [256], [0, 255])
+            plt.plot(hist, color=c)
+            plt.xlim([0, 255])
+        plt.savefig(img_path)
+        try:
+            data = {'state': 'static/media/'+name}
+        except:
+            data = {'state': 0}
+        return JsonResponse(data)
+
+
+# 分段线性处理
+def piecewiseLinearProcessing(request):
+    # 定义图像数据的路径
+    if request.method == 'POST':
+        image = request.FILES.get('picture')
+        name = image.name
+        img_path = settings.MEDIA_ROOT + '/' + name
+        with open(img_path, 'wb') as pic:
+            for c in image.chunks():
+                pic.write(c)
+        img = cv2.imread(img_path, 0)
+        h, w = img.shape[:2]
+        out = np.zeros(img.shape, np.uint8)
+        for i in range(h):
+            for j in range(w):
+                pix = img[i][j]
+                if pix < 50:
+                    out[i][j] = 0.5 * pix
+                elif pix < 150:
+                    out[i][j] = 3.6 * pix - 310
+                else:
+                    out[i][j] = 0.238 * pix + 194
+        out = np.around(out)
+        out = out.astype(np.uint8)
+        cv2.imwrite(img_path, out)
+        try:
+            data = {'state': 'static/media/'+name}
+        except:
+            data = {'state': 0}
+        return JsonResponse(data)
+
+
+# 放大图像至原来的两倍，使用双线性插值法????
+def enlarge(request):
+    # 定义图像数据的路径
+    if request.method == 'POST':
+        image = request.FILES.get('picture')
+        name = image.name
+        img_path = settings.MEDIA_ROOT + '/' + name
+        with open(img_path, 'wb') as pic:
+            for c in image.chunks():
+                pic.write(c)
+        img = cv2.imread(img_path)
+        l, w, h = img.shape
+        img = cv2.resize(img, (0, 0), fx=2, fy=2, interpolation=cv2.INTER_LINEAR)
+        cv2.imwrite(img_path, img)
+        try:
+            data = {'state': 'static/media/'+name}
+        except:
+            data = {'state': 0}
+        return JsonResponse(data)
+
+
+# 图片平移 构建移动矩阵,x轴左移 10 个像素，y轴下移 30 个
+def move(request):
+    if request.method == 'POST':
+        image = request.FILES.get('picture')
+        name = image.name
+        img_path = settings.MEDIA_ROOT + '/' + name
+        with open(img_path, 'wb') as pic:
+            for c in image.chunks():
+                pic.write(c)
+        img = cv2.imread(img_path)
+        height, width, channel = img.shape
+        M = np.float32([[1, 0, 30], [0, 1, 60]])
+        img = cv2.warpAffine(img, M, (width, height))
+        cv2.imwrite(img_path, img)
+        try:
+            data = {'state': 'static/media/' + name}
+        except:
+            data = {'state': 0}
+        return JsonResponse(data)
+
+
+# 构建矩阵，旋转中心坐标为处理后图片长宽的一半，旋转角度为45度，缩放因子为1
+def spin(request):
+    if request.method == 'POST':
+        image = request.FILES.get('picture')
+        name = image.name
+        img_path = settings.MEDIA_ROOT + '/' + name
+        with open(img_path, 'wb') as pic:
+            for c in image.chunks():
+                pic.write(c)
+        img = cv2.imread(img_path)
+        height, width, channel = img.shape
+        rows, cols, depth = img.shape
+        M = cv2.getRotationMatrix2D((cols / 2, rows / 2), 45, 1)
+        dst = cv2.warpAffine(img, M, (width, height))
+        cv2.imwrite(img_path, dst)
+        try:
+            data = {'state': 'static/media/' + name}
+        except:
+            data = {'state': 0}
+        return JsonResponse(data)
+
+
+# 水平翻转
+def horizontalFlip(request):
+    if request.method == 'POST':
+        image = request.FILES.get('picture')
+        name = image.name
+        img_path = settings.MEDIA_ROOT + '/' + name
+        with open(img_path, 'wb') as pic:
+            for c in image.chunks():
+                pic.write(c)
+        img = cv2.imread(img_path)
+        horizontal = cv2.flip(img, 1, dst=None)
+        cv2.imwrite(img_path, horizontal)
+        try:
+            data = {'state': 'static/media/' + name}
+        except:
+            data = {'state': 0}
+        return JsonResponse(data)
+
+
+# 垂直翻转
+def verticalFlip(request):
+    if request.method == 'POST':
+        image = request.FILES.get('picture')
+        name = image.name
+        img_path = settings.MEDIA_ROOT + '/' + name
+        with open(img_path, 'wb') as pic:
+            for c in image.chunks():
+                pic.write(c)
+        img = cv2.imread(img_path)
+        vertical = cv2.flip(img, 0, dst=None)
+        cv2.imwrite(img_path, vertical)
+        try:
+            data = {'state': 'static/media/' + name}
+        except:
+            data = {'state': 0}
+        return JsonResponse(data)
+
+
+# 对角线翻转
+def crossFlip(request):
+    if request.method == 'POST':
+        image = request.FILES.get('picture')
+        name = image.name
+        img_path = settings.MEDIA_ROOT + '/' + name
+        with open(img_path, 'wb') as pic:
+            for c in image.chunks():
+                pic.write(c)
+        img = cv2.imread(img_path)
+        cross = cv2.flip(img, -1, dst=None)
+        cv2.imwrite(img_path, cross)
+        try:
+            data = {'state': 'static/media/' + name}
+        except:
+            data = {'state': 0}
+        return JsonResponse(data)
+
+
+# 仿射变换
+def affineTransformation(request):
+    if request.method == 'POST':
+        image = request.FILES.get('picture')
+        name = image.name
+        img_path = settings.MEDIA_ROOT + '/' + name
+        with open(img_path, 'wb') as pic:
+            for c in image.chunks():
+                pic.write(c)
+        img = cv2.imread(img_path)
+        img = cv2.resize(img, (256, 256))
+        rows, cols = img.shape[: 2]
+        # 设置图像仿射变化矩阵
+        post1 = np.float32([[50, 50], [200, 50], [50, 200]])
+        post2 = np.float32([[10, 100], [200, 50], [100, 250]])
+        M = cv2.getAffineTransform(post1, post2)
+        # 图像仿射变换，及保存
+        result = cv2.warpAffine(img, M, (rows, cols))
+        cv2.imwrite(img_path, result)
+        try:
+            data = {'state': 'static/media/' + name}
+        except:
+            data = {'state': 0}
+        return JsonResponse(data)
+
+
+# 图片增强
+def enhance(request):
+    if request.method == 'POST':
+        image = request.FILES.get('picture')
+        name = image.name
+        img_path = settings.MEDIA_ROOT + '/' + name
+        with open(img_path, 'wb') as pic:
+            for c in image.chunks():
+                pic.write(c)
+        # 1. 灰度模式读取图像，图像名为CRH
+        CRH = cv2.imread(img_path, 0)
+
+        # 2. 计算图像梯度。首先要对读取的图像进行数据变换，因为使用了
+        # numpy对梯度进行数值计算，所以要使用
+        # CRH.astype('float')进行数据格式变换。
+        row, col = CRH.shape
+        CRH_f = np.copy(CRH)
+        CRH_f = CRH_f.astype('float')
+        gradient = np.zeros((row, col))
+        for x in range(row - 1):
+            for y in range(col - 1):
+                gx = abs(CRH_f[x + 1, y] - CRH_f[x, y])
+                gy = abs(CRH_f[x, y + 1] - CRH_f[x, y])
+                gradient[x, y] = gx + gy
+        # 3. 对图像进行增强，增强后的图像变量名为sharp
+        sharp = CRH_f + gradient
+        sharp = np.where(sharp > 255, 255, sharp)
+        sharp = np.where(sharp < 0, 0, sharp)
+        # 数据类型变换
+        gradient = gradient.astype('uint8')
+        sharp = sharp.astype('uint8')
+        cv2.imwrite(img_path, sharp)
+        try:
+            data = {'state': 'static/media/' + name}
+        except:
+            data = {'state': 0}
+        return JsonResponse(data)
+
+
+# robs算子图片增强
+def robs(request):
+    if request.method == 'POST':
+        image = request.FILES.get('picture')
+        name = image.name
+        img_path = settings.MEDIA_ROOT + '/' + name
+        with open(img_path, 'wb') as pic:
+            for c in image.chunks():
+                pic.write(c)
+        img = cv2.imread(img_path)
+        # 1. 灰度化处理图像
+        gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
+        # 2. Roberts算子
+        kernelx = np.array([[-1, 0], [0, 1]], dtype=int)
+        kernely = np.array([[0, -1], [1, 0]], dtype=int)
+        # 3. 卷积操作
+        x = cv2.filter2D(gray, cv2.CV_16S, kernelx)
+        y = cv2.filter2D(gray, cv2.CV_16S, kernely)
+        # 4. 数据格式转换
+        absx = cv2.convertScaleAbs(x)
+        absy = cv2.convertScaleAbs(y)
+        Roberts = cv2.addWeighted(absx, 0.5, absy, 0.5, 0)
+        cv2.imwrite(img_path, Roberts)
+        try:
+            data = {'state': 'static/media/' + name}
+        except:
+            data = {'state': 0}
+        return JsonResponse(data)
+
+
+# 使用 Sobel 算子提取边缘
+def sob(request):
+    if request.method == 'POST':
+        image = request.FILES.get('picture')
+        name = image.name
+        img_path = settings.MEDIA_ROOT + '/' + name
+        with open(img_path, 'wb') as pic:
+            for c in image.chunks():
+                pic.write(c)
+        img = cv2.imread(img_path)
+        # 1. 灰度化处理图像
+        gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
+        # 2. 求Sobel 算子
+        sx = cv2.Sobel(gray, cv2.CV_16S, 1, 0)
+        sy = cv2.Sobel(gray, cv2.CV_16S, 0, 1)
+        # 3. 数据格式转换
+        absx = cv2.convertScaleAbs(sx)
+        absy = cv2.convertScaleAbs(sy)
+        # 4. 组合图像
+        Sobel = cv2.addWeighted(absx, 0.5, absy, 0.5, 0)
+        cv2.imwrite(img_path, Sobel)
+        try:
+            data = {'state': 'static/media/' + name}
+        except:
+            data = {'state': 0}
+        return JsonResponse(data)
+
+
+# 使用 Laplacian 算子提取边缘
+def lap(request):
+    if request.method == 'POST':
+        image = request.FILES.get('picture')
+        name = image.name
+        img_path = settings.MEDIA_ROOT + '/' + name
+        with open(img_path, 'wb') as pic:
+            for c in image.chunks():
+                pic.write(c)
+        img = cv2.imread(img_path)
+        # 1. 灰度化处理图像
+        gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
+        # 2. 高斯滤波
+        grayG = cv2.GaussianBlur(gray, (5, 5), 0)
+        fltI = cv2.Laplacian(grayG, cv2.CV_16S, ksize=3)
+        # 3. 拉普拉斯算法
+        Laplacian = cv2.convertScaleAbs(fltI)
+        cv2.imwrite(img_path, Laplacian)
+        try:
+            data = {'state': 'static/media/' + name}
+        except:
+            data = {'state': 0}
+        return JsonResponse(data)
+
+
+# 使用 LoG 算子提取边缘
+def log(request):
+    if request.method == 'POST':
+        image = request.FILES.get('picture')
+        name = image.name
+        img_path = settings.MEDIA_ROOT + '/' + name
+        with open(img_path, 'wb') as pic:
+            for c in image.chunks():
+                pic.write(c)
+        img = cv2.imread(img_path)
+        gray = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
+        gray = cv2.copyMakeBorder(gray, 2, 2, 2, 2, borderType=cv2.BORDER_REPLICATE)
+        image = cv2.GaussianBlur(gray, (3, 3), 0, 0)
+        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]])
+        row = image.shape[0]
+        col = image.shape[1]
+        image1 = np.zeros(image.shape)
+        for i in range(2, row - 2):
+            for j in range(2, col - 2):
+                image1[i, j] = np.sum(m1 * image[i - 2:i + 3, j - 2:j + 3, 1])
+        image1 = cv2.convertScaleAbs(image1)
+        cv2.imwrite(img_path, image1)
+        try:
+            data = {'state': 'static/media/' + name}
+        except:
+            data = {'state': 0}
+        return JsonResponse(data)
+
+
+# Canny 边缘检测过程
+def cny(request):
+    if request.method == 'POST':
+        image = request.FILES.get('picture')
+        name = image.name
+        img_path = settings.MEDIA_ROOT + '/' + name
+        with open(img_path, 'wb') as pic:
+            for c in image.chunks():
+                pic.write(c)
+        src = cv2.imread(img_path)
+        blur = cv2.GaussianBlur(src, (3, 3), 0)
+
+        gray = cv2.cvtColor(blur, cv2.COLOR_BGR2GRAY)
+
+        gradx = cv2.Sobel(gray, cv2.CV_16SC1, 1, 0)
+        grady = cv2.Sobel(gray, cv2.CV_16SC1, 0, 1)
+        edge_output = cv2.Canny(gradx, grady, 50, 150)
+        cv2.imwrite(img_path, edge_output)
+        try:
+            data = {'state': 'static/media/' + name}
+        except:
+            data = {'state': 0}
+        return JsonResponse(data)
+
+
+# 均值滤波器
+def MeanFilter(request):
+    if request.method == 'POST':
+        image = request.FILES.get('picture')
+        name = image.name
+        img_path = settings.MEDIA_ROOT + '/' + name
+        with open(img_path, 'wb') as pic:
+            for c in image.chunks():
+                pic.write(c)
+        img = cv2.imread(img_path)
+        gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
+        w = gray.shape[1]
+        h = gray.shape[0]
+        newing = np.array(gray)
+
+        lbing = np.zeros((h + 2, w + 2), np.float32)
+        tmping = np.zeros((h + 2, w + 2))
+        myh = h + 2
+        myw = w + 2
+        tmping[1:myh - 1, 1:myw - 1] = newing[0:h, 0:w]
+
+        a = 1 / 8.0
+        kernel = a * np.array([[1, 1, 1], [1, 0, 1], [1, 1, 1]])
+        for y in range(1, myh - 1):
+            for x in range(1, myw - 1):
+                lbing[y, x] = np.sum(kernel * tmping[y - 1:y + 2, x - 1:x + 2])
+
+        result = np.array(lbing[1:myh - 1, 1:myw - 1], np.uint8)
+        cv2.imwrite(img_path, result)
+        try:
+            data = {'state': 'static/media/' + name}
+        except:
+            data = {'state': 0}
+        return JsonResponse(data)
+
+
+# 中值滤波器
+def MedFilter(request):
+    if request.method == 'POST':
+        image = request.FILES.get('picture')
+        name = image.name
+        img_path = settings.MEDIA_ROOT + '/' + name
+        with open(img_path, 'wb') as pic:
+            for c in image.chunks():
+                pic.write(c)
+        img = cv2.imread(img_path)
+        w = img.shape[1]
+        h = img.shape[0]
+        median = np.array(img)
+        for y in range(1, w):
+            for x in range(1, h):
+                median[x, y] = np.median(img[x - 1:x + 2, y - 1:y + 2])
+        cv2.imwrite(img_path, median)
+        try:
+            data = {'state': 'static/media/' + name}
+        except:
+            data = {'state': 0}
+        return JsonResponse(data)
+
+
+# Hough线段变化
+def HoughLineChange(request):
+    if request.method == 'POST':
+        image = request.FILES.get('picture')
+        name = image.name
+        img_path = settings.MEDIA_ROOT + '/' + name
+        with open(img_path, 'wb') as pic:
+            for c in image.chunks():
+                pic.write(c)
+        img = cv2.imread(img_path)
+        img = cv2.GaussianBlur(img, (3, 3), 0)
+        edges = cv2.Canny(img, 50, 150, apertureSize=3)
+        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)
+
+
+        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)
+
+        cv2.waitKey(0)
+        cv2.destroyAllWindows()
+        cv2.imwrite(img_path, result_P)
+        try:
+            data = {'state': 'static/media/' + name}
+        except:
+            data = {'state': 0}
+        return JsonResponse(data)
+
+
+# 腐蚀
+def erode(request):
+    if request.method == 'POST':
+        image = request.FILES.get('picture')
+        name = image.name
+        img_path = settings.MEDIA_ROOT + '/' + name
+        with open(img_path, 'wb') as pic:
+            for c in image.chunks():
+                pic.write(c)
+        img = cv2.imread(img_path)
+        src = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
+
+        # 使用一个5x5的交叉型结构元（核心在几何中心）对二值图片src进行腐蚀
+        kernel = cv2.getStructuringElement(cv2.MORPH_CROSS, (5, 5))
+        erosion = cv2.erode(src, kernel)
+        cv2.imwrite(img_path, erosion)
+        try:
+            data = {'state': 'static/media/' + name}
+        except:
+            data = {'state': 0}
+        return JsonResponse(data)
+
+
+# 膨胀
+def dialate(request):
+    if request.method == 'POST':
+        image = request.FILES.get('picture')
+        name = image.name
+        img_path = settings.MEDIA_ROOT + '/' + name
+        with open(img_path, 'wb') as pic:
+            for c in image.chunks():
+                pic.write(c)
+        img = cv2.imread(img_path)
+        src = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
+
+        # 使用一个5x5的交叉型结构元（核心在几何中心）对二值图片src进行膨胀
+        kernel = cv2.getStructuringElement(cv2.MORPH_CROSS, (5, 5))
+        dilation = cv2.dilate(src, kernel)
+        cv2.imwrite(img_path, dilation)
+        try:
+            data = {'state': 'static/media/' + name}
+        except:
+            data = {'state': 0}
+        return JsonResponse(data)
+
+
+# 开操作######
+def openMorphing(request):
+    if request.method == 'POST':
+        image = request.FILES.get('picture')
+        name = image.name
+        img_path = settings.MEDIA_ROOT + '/' + name
+        with open(img_path, 'wb') as pic:
+            for c in image.chunks():
+                pic.write(c)
+        img = cv2.imread(img_path)
+        gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
+        retval, dst = cv2.threshold(gray, 127, 255, cv2.THRESH_BINARY)
+
+        #   定义十字形结构元素
+        kernel = cv2.getStructuringElement(cv2.MORPH_CROSS,(10,10))
+
+        im_op = cv2.morphologyEx(dst, cv2.MORPH_OPEN,kernel)
+        cv2.imwrite(img_path, im_op)
+        try:
+            data = {'state': 'static/media/' + name}
+        except:
+            data = {'state': 0}
+        return JsonResponse(data)
+
+
+# 闭操作
+def closeMorphing(request):
+    if request.method == 'POST':
+        image = request.FILES.get('picture')
+        name = image.name
+        img_path = settings.MEDIA_ROOT + '/' + name
+        with open(img_path, 'wb') as pic:
+            for c in image.chunks():
+                pic.write(c)
+        img = cv2.imread(img_path)
+        gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
+        retval, dst = cv2.threshold(gray, 127, 255, cv2.THRESH_BINARY)
+
+        #   定义十字形结构元素
+        kernel = cv2.getStructuringElement(cv2.MORPH_CROSS, (10, 10))
+
+        im_cl = cv2.morphologyEx(dst, cv2.MORPH_CLOSE, kernel)
+        cv2.imwrite(img_path, im_cl)
+        try:
+            data = {'state': 'static/media/' + name}
+        except:
+            data = {'state': 0}
+        return JsonResponse(data)
+
+
+# 雪花噪声
+def sp_noise(request):
+    if request.method == 'POST':
+        image = request.FILES.get('picture')
+        name = image.name
+        img_path = settings.MEDIA_ROOT + '/' + name
+        with open(img_path, 'wb') as pic:
+            for c in image.chunks():
+                pic.write(c)
+        img = cv2.imread(img_path)
+        prob = 0.2
+        # 待输出的图片
+        output = np.zeros(img.shape, np.uint8)
+
+        # 遍历图像，获取叠加噪声后的图像
+        thres = 1 - prob
+        for i in range(img.shape[0]):
+            for j in range(img.shape[1]):
+                rdn = random.random()
+                if rdn < prob:
+                    output[i][j] = 0
+                elif rdn > thres:
+                    output[i][j] = 255
+                else:
+                    output[i][j] = img[i][j]
+        cv2.imwrite(img_path, output)
+        try:
+            data = {'state': 'static/media/' + name}
+        except:
+            data = {'state': 0}
+        return JsonResponse(data)
+
+
+# 添加高斯噪声,mean : 均值 , var : 方差
+def gasuss_noise(request):
+    if request.method == 'POST':
+        image = request.FILES.get('picture')
+        name = image.name
+        img_path = settings.MEDIA_ROOT + '/' + name
+        with open(img_path, 'wb') as pic:
+            for c in image.chunks():
+                pic.write(c)
+        img = cv2.imread(img_path)
+        image = np.array(img / 255, dtype=float)
+        var = 0.001
+        mean = 0
+        noise = np.random.normal(mean, var ** 0.5, image.shape)
+        out = image + noise
+        if out.min() < 0:
+            low_clip = -1.
+        else:
+            low_clip = 0.
+        out = np.clip(out, low_clip, 1.0)
+        out = np.uint8(out * 255)
+        cv2.imwrite(img_path, out)
+        try:
+            data = {'state': 'static/media/' + name}
+        except:
+            data = {'state': 0}
+        return JsonResponse(data)
+
+
+# 高通滤波
+def highPassFilter(request):
+    if request.method == 'POST':
+        image = request.FILES.get('picture')
+        name = image.name
+        img_path = settings.MEDIA_ROOT + '/' + name
+        with open(img_path, 'wb') as pic:
+            for c in image.chunks():
+                pic.write(c)
+        img = cv2.imread(img_path)
+        image = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
+        output = np.zeros(image.shape, np.uint8)
+
+        for i in range(image.shape[0]):
+            for j in range(image.shape[1]):
+                if 200 < image[i][j]:
+                    output[i][j] = image[i][j]
+                else:
+                    output[i][j] = 0
+        cv2.imwrite(img_path, output)
+        try:
+            data = {'state': 'static/media/' + name}
+        except:
+            data = {'state': 0}
+        return JsonResponse(data)
+
+
+##########
+##########
+# 空域锐化
+##########
+#########
+
+
+# Roberts因子锐化
+def Roberts(image):
+    if request.method == 'POST':
+        image = request.FILES.get('picture')
+        name = image.name
+        img_path = settings.MEDIA_ROOT + '/' + name
+        with open(img_path, 'wb') as pic:
+            for c in image.chunks():
+                pic.write(c)
+        img = cv2.imread(img_path)
+        img = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
+        img_Roberts = np.zeros(img.shape, dtype=int)
+        for i in range(1, img.shape[0] - 1):  # 第一列和最后一列不用处理
+            for j in range(1, img.shape[1] - 1):
+                img_Roberts[i][j] = abs((int)(img[i + 1][j + 1]) - (int)(img[i][j])) + abs(
+                    (int)(img[i + 1][j]) - (int)(img[i][j + 1]))
+        result = np.array(img_Roberts)
+        plt.subplot(244), plt.title("4.Roberts锐化后"), plt.axis('off')
+        plt.imshow(img_Roberts, cmap="gray")
+        plt.show()
+
+
+def sharpen(request):
+    if request.method == 'POST':
+        image = request.FILES.get('picture')
+        name = image.name
+        img_path = settings.MEDIA_ROOT + '/' + name
+        with open(img_path, 'wb') as pic:
+            for c in image.chunks():
+                pic.write(c)
+        img = cv2.imread(img_path)
+        kernel = np.array([[0, -1, 0], [-1, 5, -1], [0, -1, 0]], np.float32)  # 锐化
+        dst = cv2.filter2D(img, -1, kernel=kernel)
+        cv2.imwrite(img_path, dst)
+        try:
+            data = {'state': 'static/media/' + name}
+        except:
+            data = {'state': 0}
+        return JsonResponse(data)
+
+
+##########
+##########
+# 频域锐化
+##########
+#########
+
+# 理想低通滤波
+def IdealLowPassFiltering(request):
+    if request.method == 'POST':
+        image = request.FILES.get('picture')
+        name = image.name
+        img_path = settings.MEDIA_ROOT + '/' + name
+        with open(img_path, 'wb') as pic:
+            for c in image.chunks():
+                pic.write(c)
+        img = cv2.imread(img_path)
+        f_shift = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
+        # 设置滤波半径
+        D0 = 80
+        # 初始化
+        m = f_shift.shape[0]
+        n = f_shift.shape[1]
+        h1 = np.zeros((m, n))
+        x0 = np.floor(m / 2)
+        y0 = np.floor(n / 2)
+        for i in range(m):
+            for j in range(n):
+                D = np.sqrt((i - x0) ** 2 + (j - y0) ** 2)
+                if D <= D0:
+                    h1[i][j] = 1
+        result = np.multiply(f_shift, h1)
+        cv2.imwrite(img_path, result)
+        try:
+            data = {'state': 'static/media/' + name}
+        except:
+            data = {'state': 0}
+        return JsonResponse(data)
+
+
+# Butterworth低通滤波器
+def butterworth_low_filter(request):
+    """
+        生成一个Butterworth低通滤波器（并返回）
+    """
+    if request.method == 'POST':
+        image = request.FILES.get('picture')
+        name = image.name
+        img_path = settings.MEDIA_ROOT + '/' + name
+        with open(img_path, 'wb') as pic:
+            for c in image.chunks():
+                pic.write(c)
+        img = cv2.imread(img_path)
+        D0 = 20
+        rank = 2
+        h, w = img.shape[:2]
+        filter_img = np.zeros((h, w))
+        u = np.fix(h / 2)
+        v = np.fix(w / 2)
+        for i in range(h):
+            for j in range(w):
+                d = np.sqrt((i - u) ** 2 + (j - v) ** 2)
+                filter_img[i, j] = 1 / (1 + 0.414 * (d / D0) ** (2 * rank))
+        cv2.imwrite(img_path, filter_img)
+        try:
+            data = {'state': 'static/media/' + name}
+        except:
+            data = {'state': 0}
+        return JsonResponse(data)
+
+
+##########
+##########
+# 频域平滑
+##########
+#########
+
+
+# 理想高通滤波
+def IdealHighPassFiltering(request):
+    if request.method == 'POST':
+        image = request.FILES.get('picture')
+        name = image.name
+        img_path = settings.MEDIA_ROOT + '/' + name
+        with open(img_path, 'wb') as pic:
+            for c in image.chunks():
+                pic.write(c)
+        img = cv2.imread(img_path)
+        f_shift = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
+        # 设置滤波半径
+        D0 = 80
+        # 初始化
+        m = f_shift.shape[0]
+        n = f_shift.shape[1]
+        h1 = np.zeros((m, n))
+        x0 = np.floor(m / 2)
+        y0 = np.floor(n / 2)
+        for i in range(m):
+            for j in range(n):
+                D = np.sqrt((i - x0) ** 2 + (j - y0) ** 2)
+                if D >= D0:
+                    h1[i][j] = 1
+        result = np.multiply(f_shift, h1)
+        cv2.imwrite(img_path, result)
+        try:
+            data = {'state': 'static/media/' + name}
+        except:
+            data = {'state': 0}
+        return JsonResponse(data)
+
+
+# Butterworth高通滤波器
+def butterworth_high_filter(request):
+    """
+        生成一个Butterworth高通滤波器（并返回）
+    """
+    if request.method == 'POST':
+        image = request.FILES.get('picture')
+        name = image.name
+        img_path = settings.MEDIA_ROOT + '/' + name
+        with open(img_path, 'wb') as pic:
+            for c in image.chunks():
+                pic.write(c)
+        img = cv2.imread(img_path)
+        D0 = 40
+        rank = 2
+        h, w = img.shape[:2]
+        filter_img = np.zeros((h, w))
+        u = np.fix(h / 2)
+        v = np.fix(w / 2)
+        for i in range(h):
+            for j in range(w):
+                d = np.sqrt((i - u) ** 2 + (j - v) ** 2)
+                filter_img[i, j] = 1 / (1 + (D0 / d) ** (2 * rank))
+        cv2.imwrite(img_path, filter_img)
+        try:
+            data = {'state': 'static/media/' + name}
+        except:
+            data = {'state': 0}
+        return JsonResponse(data)

djangoProject/wsgi.py

@@ -0,0 +1,18 @@
+"""
+WSGI config for djangoProject project.
+
+It exposes the WSGI callable as a module-level variable named ``application``.
+
+For more information on this file, see
+https://docs.djangoproject.com/en/4.0/howto/deployment/wsgi/
+"""
+
+import os
+
+from django.core.wsgi import get_wsgi_application
+
+os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'djangoProject.settings')
+
+application = get_wsgi_application()
+
+

manage.py

@@ -0,0 +1,22 @@
+#!/usr/bin/env python
+"""Django's command-line utility for administrative tasks."""
+import os
+import sys
+
+
+def main():
+    """Run administrative tasks."""
+    os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'djangoProject.settings')
+    try:
+        from django.core.management import execute_from_command_line
+    except ImportError as exc:
+        raise ImportError(
+            "Couldn't import Django. Are you sure it's installed and "
+            "available on your PYTHONPATH environment variable? Did you "
+            "forget to activate a virtual environment?"
+        ) from exc
+    execute_from_command_line(sys.argv)
+
+
+if __name__ == '__main__':
+    main()

templates/upload.html

@@ -0,0 +1,97 @@
+<!DOCTYPE html>
+<html lang="en">
+<head>
+    <meta charset="UTF-8">
+    <title>Title</title>
+</head>
+<body>
+    <form enctype="multipart/form-data">
+        {% csrf_token %}
+        <img id="image" width="700" height="500" />
+        <br/>
+        <input type="file" onchange="selectImage(this);" name="picture" id="picture"/>
+        <br/>
+        <input id="submit-btn" type="button" value="提交">
+    </form>
+    <div>
+        <label>处理方式</label>
+        <select id="select">
+            <option id="histogram" value="histogram">直方图</option>
+            <option id="greyHistogram" value="greyHistogram">灰度直方图</option>
+            <option id="colorHistogram" value="colorHistogram">彩色直方图</option>
+            <option id="piecewiseLinearProcessing" value="piecewiseLinearProcessing">分段线性处理</option>
+            <option id="enlarge" value="enlarge">放大</option>
+            <option id="move" value="move">平移</option>
+            <option id="spin" value="spin">旋转</option>
+            <option id="horizontalFlip" value="horizontalFlip">水平镜像</option>
+            <option id="verticalFlip" value="verticalFlip">垂直镜像</option>
+            <option id="crossFlip" value="crossFlip">对角线镜像</option>
+            <option id="affineTransformation" value="affineTransformation">仿射变换</option>
+            <option id="enhance" value="enhance">图片增强</option>
+            <option id="robs" value="robs">使用 Roberts 算法提取图像边缘</option>
+            <option id="sob" value="sob">使用 Sobel 算子提取边缘。</option>
+            <option id="lap" value="lap">使用 Laplacian 算子提取边缘</option>
+            <option id="log" value="log">使用 LoG 算子提取边缘</option>
+            <option id="cny" value="cny">使用Canny 算子提取边缘</option>
+            <option id="MeanFilter" value="MeanFilter">均值滤波器</option>
+            <option id="MedFilter" value="MedFilter">中值滤波器</option>
+            <option id="HoughLineChange" value="HoughLineChange">Hough线段变化</option>
+            <option id="erode" value="erode">腐蚀</option>
+            <option id="dialate" value="dialate">膨胀</option>
+            <option id="sp_noise" value="sp_noise">雪花噪声</option>
+            <option id="gasuss_noise" value="gasuss_noise">高斯噪声</option>
+            <option id="highPassFilter" value="highPassFilter">高通滤波</option>
+            <option id="IdealLowPassFiltering" value="IdealLowPassFiltering">理想低通滤波</option>
+            <option id="butterworth_low_filter" value="butterworth_low_filter">Butterworth低通滤波器</option>
+            <option id="IdealHighPassFiltering" value="IdealHighPassFiltering">理想高通滤波</option>
+            <option id="butterworth_high_filter" value="butterworth_high_filter">Butterworth高通滤波器</option>
+            <option id="sharpen" value="sharpen">锐化</option>
+
+        </select>
+    </div>
+    <script src="https://cdn.bootcss.com/jquery/3.2.1/jquery.min.js"></script>
+    <script>
+    $('#submit-btn').on('click',function () {
+        var formData = new FormData();
+        var select = document.getElementById("select")
+        var url='/'+select.options[select.selectedIndex].value+'/'
+        formData.append("picture",$("#picture")[0].files[0]);
+        formData.append("csrfmiddlewaretoken",$("[name='csrfmiddlewaretoken']").val());
+        $.ajax({
+            processData:false,
+            contentType:false,
+            url:url,
+            type:'post',
+            data:formData,
+            success:function (arg) {
+                if (arg.state === 0){
+                    alert('提交失败')
+                }
+                else {
+                    alert('提交成功')
+                    var picture=document.getElementById("image")
+                    picture.src=arg.state
+                }
+            }
+        })
+    });
+    </script>
+    <script>
+        let image = '';
+
+        function selectImage(file) {
+                if (!file.files || !file.files[0]) {
+                    return;
+                }
+                var reader = new FileReader();
+                reader.onload = function (evt) {
+                    document.getElementById('image').src = evt.target.result;
+                    image = evt.target.result;
+                }
+                reader.readAsDataURL(file.files[0]);
+            }
+    </script>
+</body>
+</html>
+
+