add image test

Clarity Test/.ipynb_checkpoints/Untitled-checkpoint.ipynb

@@ -0,0 +1,153 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "id": "bc5d3202-7004-4a30-9688-d590b7ff40ff",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import cv2\n",
+    "import numpy as np"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "afcaafc9-bc9d-4b6e-a000-7daae79ca33c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def image_blur(image):\n",
+    "    if image is None:\n",
+    "        raise ValueError(\"Image is not loaded correctly.\")\n",
+    "    # 高斯模糊\n",
+    "    gaussian_blur = cv2.GaussianBlur(image, (15, 15), 0)\n",
+    "    # 均值模糊\n",
+    "    mean_blur = cv2.blur(image, (15, 15))\n",
+    "    # 中值模糊\n",
+    "    median_blur = cv2.medianBlur(image, 15)\n",
+    "    return gaussian_blur,mean_blur,median_blur"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "id": "34a40ed3-6050-4161-ba30-8156473f8078",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Error: Image not found or unable to load.\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "[ WARN:0@1179.199] global loadsave.cpp:268 findDecoder imread_('002.png'): can't open/read file: check file path/integrity\n"
+     ]
+    }
+   ],
+   "source": [
+    "image_path = '002.png'\n",
+    "image = cv2.imread(image_path)\n",
+    "if image is None:\n",
+    "    raise ValueError(\"Error: Image not found or unable to load.\")\n",
+    "\n",
+    "\n",
+    "    # gaussian_blur, mean_blur, median_blur = image_blur(image)\n",
+    "    # cv2.imwrite('gaussian_blur.jpg', gaussian_blur)\n",
+    "    # cv2.imwrite('mean_blur.jpg', mean_blur)\n",
+    "    # cv2.imwrite('median_blur.jpg', median_blur)\n",
+    "# gaussian_blur,mean_blur,median_blur=image_blur(image)\n",
+    "# cv2.imwrite('123', image)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a745fe14-a960-4668-bd98-c17025619f1b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def brenner(image):\n",
+    "    gradient = np.zeros_like(image, dtype=np.float32)\n",
+    "    gradient[:-2, :] = image[2:, :] - image[:-2, :]\n",
+    "    return np.var(gradient)\n",
+    "\n",
+    "# 计算清晰度\n",
+    "brenner_original = brenner(cv2.cvtColor(image, cv2.COLOR_BGR2GRAY))\n",
+    "brenner_gaussian = brenner(cv2.cvtColor(gaussian_blur, cv2.COLOR_BGR2GRAY))\n",
+    "brenner_mean = brenner(cv2.cvtColor(mean_blur, cv2.COLOR_BGR2GRAY))\n",
+    "brenner_median = brenner(cv2.cvtColor(median_blur, cv2.COLOR_BGR2GRAY))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "id": "45a1739c-20fe-4df8-b703-732c23ff3400",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "[ WARN:0@1400.488] global loadsave.cpp:268 findDecoder imread_('002.png'): can't open/read file: check file path/integrity\n"
+     ]
+    },
+    {
+     "ename": "ValueError",
+     "evalue": "Error: Image not found or unable to load.",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
+      "Cell \u001b[0;32mIn[25], line 6\u001b[0m\n\u001b[1;32m      4\u001b[0m image \u001b[38;5;241m=\u001b[39m cv2\u001b[38;5;241m.\u001b[39mimread(image_path)\n\u001b[1;32m      5\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m image \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m----> 6\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mError: Image not found or unable to load.\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m      7\u001b[0m cv2\u001b[38;5;241m.\u001b[39mimwrite(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m123.png\u001b[39m\u001b[38;5;124m'\u001b[39m, image)\n",
+      "\u001b[0;31mValueError\u001b[0m: Error: Image not found or unable to load."
+     ]
+    }
+   ],
+   "source": [
+    "import cv2\n",
+    "\n",
+    "image_path = '002.png'\n",
+    "image = cv2.imread(image_path)\n",
+    "if image is None:\n",
+    "    raise ValueError(\"Error: Image not found or unable to load.\")\n",
+    "cv2.imwrite('123.png', image)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "1f645692-aca6-4701-8382-99b993eef448",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "pmn_env",
+   "language": "python",
+   "name": "pmn_env"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.16"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

Clarity Test/.ipynb_checkpoints/test-checkpoint.py

@@ -0,0 +1,7 @@
+import cv2
+
+image_path = '002.png'
+image = cv2.imread(image_path)
+if image is None:
+    raise ValueError("Error: Image not found or unable to load.")
+cv2.imwrite('123.png', image)

Clarity Test/image_test.py

@@ -0,0 +1,185 @@
+import os
+import cv2
+import numpy as np
+
+# 高斯模糊
+def image_blur(image,ksize):
+    if image is None:
+        raise ValueError("Image is not loaded correctly.")
+    gaussian_blur = cv2.GaussianBlur(image, (ksize, ksize), 0)
+    return gaussian_blur
+
+# 椒盐噪声
+def add_salt_pepper(image, salt_prob=0.05, pepper_prob=0.05):
+    noisy = image.copy()
+    # 添加盐噪声
+    salt = np.random.randint(0, 256, size=image.shape[:2])
+    noisy[salt < salt_prob*255] = 255
+    # 添加椒噪声
+    pepper = np.random.randint(0, 256, size=image.shape[:2])
+    noisy[pepper < pepper_prob*255] = 0
+    return noisy
+
+# Brenner 梯度函数计算
+def brenner(img):
+    '''
+    :param img: narray 二维灰度图像
+    :return: int 图像越清晰越大
+    '''
+    return int(np.sum((img[:-2, :] - img[2:, :]) ** 2))
+
+# Laplacian 梯度函数计算
+def Laplacian(img):
+    '''
+    :param img: narray 二维灰度图像
+    :return: int 图像越清晰越大
+    '''
+    return int(cv2.Laplacian(img, cv2.CV_64F).var())
+
+# SMD 梯度函数计算
+def SMD(img):
+    '''
+    :param img: narray 二维灰度图像
+    :return: int 图像越清晰越大
+    '''
+    diff_x = np.abs(img[1:-1, :] - img[:-2, :])
+    diff_y = np.abs(img[1:, :] - img[:-1, :])
+    return int(np.sum(diff_x) + np.sum(diff_y))
+
+# SMD2 函数计算
+def SMD2(img):
+    '''
+    :param img: narray 二维灰度图像
+    :return: int 图像越清晰越大
+    '''
+    sobel_x = cv2.Sobel(img, cv2.CV_64F, 1, 0, ksize=3)
+    sobel_y = cv2.Sobel(img, cv2.CV_64F, 0, 1, ksize=3)
+    gradient = np.abs(sobel_x) + np.abs(sobel_y)
+    return int(np.sum(gradient ** 2))
+
+# 方差函数计算
+def variance(img):
+    '''
+    :param img: narray 二维灰度图像
+    :return: int 图像越清晰越大
+    '''
+    u = np.mean(img)
+    return int(np.sum((img - u) ** 2))
+
+# Energy 函数计算
+def energy(img):
+    '''
+    :param img: narray 二维灰度图像
+    :return: int 图像越清晰越大
+    '''
+    diff_x = img[1:, :-1] - img[:-1, :-1]
+    diff_y = img[:-1, 1:] - img[:-1, :-1]
+    return int(np.sum(diff_x ** 2 * diff_y ** 2))
+
+# Vollath 函数计算
+def Vollath(img):
+    '''
+    :param img: narray 二维灰度图像
+    :return: int 图像越清晰越大
+    '''
+    u = np.mean(img)
+    return int(-img.size * (u ** 2) + np.sum(img[:-1, :] * img[1:, :]))
+
+# Entropy 函数计算
+def entropy(img):
+    '''
+    :param img: narray 二维灰度图像
+    :return: int 图像越清晰越大
+    '''
+    hist = np.bincount(img.flatten(), minlength=256)
+    p = hist / img.size
+    p = p[p > 0]
+    return int(-np.sum(p * np.log(p)))
+
+
+
+def image_test(filename,image,noisy_img,blur_image):
+    image_gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
+    noisy_gray = cv2.cvtColor(noisy_img, cv2.COLOR_BGR2GRAY)
+    blur_gray = cv2.cvtColor(blur_image, cv2.COLOR_BGR2GRAY)
+
+    # 定义一个格式化字符串，确保每个数值占据相同的宽度
+    format_str = "{:<10} {:<15} {:<15} {:<15}"
+
+    # 打印标题
+    print(format_str.format(filename, "Original", "Noisy", "Blur"))
+
+    # 打印每个指标的值
+    print(format_str.format("Brenner", brenner(image_gray), brenner(noisy_gray), brenner(blur_gray)))
+    print(format_str.format("Laplacian", Laplacian(image_gray), Laplacian(noisy_gray), Laplacian(blur_gray)))
+    print(format_str.format("SMD", SMD(image_gray), SMD(noisy_gray), SMD(blur_gray)))
+    print(format_str.format("SMD2", SMD2(image_gray), SMD2(noisy_gray), SMD2(blur_gray)))
+    print(format_str.format("Variance", variance(image_gray), variance(noisy_gray), variance(blur_gray)))
+    print(format_str.format("Energy", energy(image_gray), energy(noisy_gray), energy(blur_gray)))
+    print(format_str.format("Vollath", Vollath(image_gray), Vollath(noisy_gray), Vollath(blur_gray)))
+    print(format_str.format("Entropy", entropy(image_gray), entropy(noisy_gray), entropy(blur_gray)))
+
+
+    # print(filename,'noisy','blur')
+    # print('Brenner',brenner(image_gray),brenner(noisy_gray),brenner(blur_gray))
+    # print('Laplacian',Laplacian(image_gray),Laplacian(noisy_gray),Laplacian(blur_gray))
+    # print('SMD',SMD(image_gray), SMD(noisy_gray), SMD(blur_gray))
+    # print('SMD2',SMD2(image_gray), SMD2(noisy_gray), SMD2(blur_gray))
+    # print('Variance',variance(image_gray),variance(noisy_gray),variance(blur_gray))
+    # print('Energy',energy(image_gray),energy(noisy_gray),energy(blur_gray))
+    # print('Vollath',Vollath(image_gray),Vollath(noisy_gray),Vollath(blur_gray))
+    # print('Entropy',entropy(image_gray),entropy(noisy_gray),entropy(blur_gray))
+  
+
+
+def process_images(input_dir, salty_dir,blur_dir):
+    # 创建输出目录（如果不存在）
+    if not os.path.exists(salty_dir):
+        os.makedirs(salty_dir)
+    if not os.path.exists(blur_dir):
+        os.makedirs(blur_dir)
+    
+    # 支持的图片格式
+    img_exts = ('.jpg', '.jpeg', '.png', '.bmp', '.tif', '.tiff')
+    
+    # 遍历输入目录
+    for filename in os.listdir(input_dir):
+        if filename.lower().endswith(img_exts):
+            # 读取图片
+            img_path = os.path.join(input_dir, filename)
+            img = cv2.imread(img_path)
+            img = cv2.resize(img,(512, 512))
+
+            if img is None:
+                raise ValueError("Error: Image not found or unable to load.")
+            
+            if img is not None:
+
+                # 添加椒盐噪声
+                noisy_img = add_salt_pepper(img)
+                # 添加Gauss噪声
+                blur_image = image_blur(img,ksize=25)
+
+
+
+                # 构造新文件名
+                name, ext = os.path.splitext(filename)
+                salty_filename = f"{name}_salty{ext}"
+                blur_filename = f"{name}_blur{ext}"
+
+                image_test(filename,img,noisy_img,blur_image)
+                print('\n')
+
+
+                salty_path = os.path.join(salty_dir, salty_filename)
+                cv2.imwrite(salty_path, noisy_img)
+                blur_path = os.path.join(blur_dir, blur_filename)
+                cv2.imwrite(blur_path, blur_image)
+
+
+if __name__ == '__main__':
+    input_dir = 'data_process/Clarity Test/images/source'
+    salty_dir = 'data_process/Clarity Test/images/salty'
+    blur_dir = 'data_process/Clarity Test/images/blur'
+    process_images(input_dir, salty_dir,blur_dir)
+    

datasets/image_qualified.py

@@ -4,11 +4,12 @@ import numpy as np
 import os
 
 
-def calculate_clarity_score(image_path):
+def calculate_clarity_score(image_path,target_size=(512, 512)):
     """
     计算图片的清晰度评分
     """
     image = cv2.imread(image_path, cv2.IMREAD_GRAYSCALE)
+    image = cv2.resize(image, target_size)
     if image is None:
         raise ValueError(f"无法读取图片：{image_path}")
     return cv2.Laplacian(image, cv2.CV_64F).var()
@@ -40,9 +41,7 @@ def process_images(input_folder, output_folder,clarity_score_threshold):
                         # output_subfolder
                         relative_path = os.path.relpath(root, input_folder)
                         output_subfolder = os.path.join(output_folder, relative_path)
-                            # print(f'root: {root}, input_folder: {input_folder}, relative_path: {relative_path}, output_subfolder: {output_subfolder}')
-        
-                        
+                            # print(f'root: {root}, input_folder: {input_folder}, relative_path: {relative_path}, output_subfolder: {output_subfolder}')                        
                         if not os.path.exists(output_subfolder):
                             os.makedirs(output_subfolder)
                         output_path = os.path.join(output_subfolder, os.path.splitext(filename)[0] + ".png")
@@ -55,8 +54,8 @@ def process_images(input_folder, output_folder,clarity_score_threshold):
 
 
 if __name__ == "__main__":
-    input_folder = 'PMN_WS/data_process/datasets/source'  # 输入文件夹路径
-    output_folder = 'PMN_WS/data_process/datasets/target'  # 输出文件夹路径
+    input_folder = 'data_process/datasets/source'  # 输入文件夹路径
+    output_folder = 'data_process/datasets/target'  # 输出文件夹路径
     clarity_score_threshold =50
     process_images(input_folder, output_folder,clarity_score_threshold)