diff --git a/Clarity Test/.ipynb_checkpoints/Untitled-checkpoint.ipynb b/Clarity Test/.ipynb_checkpoints/Untitled-checkpoint.ipynb new file mode 100644 index 0000000..b8ae3a9 --- /dev/null +++ b/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 +} diff --git a/Clarity Test/.ipynb_checkpoints/test-checkpoint.py b/Clarity Test/.ipynb_checkpoints/test-checkpoint.py new file mode 100644 index 0000000..6342bf6 --- /dev/null +++ b/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) \ No newline at end of file diff --git a/Clarity Test/image_test.py b/Clarity Test/image_test.py new file mode 100644 index 0000000..a6b8f89 --- /dev/null +++ b/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) + \ No newline at end of file diff --git a/Clarity Test/images/blur/002_blur.png b/Clarity Test/images/blur/002_blur.png new file mode 100644 index 0000000..2ba3f23 Binary files /dev/null and b/Clarity Test/images/blur/002_blur.png differ diff --git a/Clarity Test/images/blur/003_blur.jpg b/Clarity Test/images/blur/003_blur.jpg new file mode 100644 index 0000000..929ea10 Binary files /dev/null and b/Clarity Test/images/blur/003_blur.jpg differ diff --git a/Clarity Test/images/blur/007_blur.png b/Clarity Test/images/blur/007_blur.png new file mode 100644 index 0000000..f1f3a29 Binary files /dev/null and b/Clarity Test/images/blur/007_blur.png differ diff --git a/Clarity Test/images/salty/002_salty.png b/Clarity Test/images/salty/002_salty.png new file mode 100644 index 0000000..825f61f Binary files /dev/null and b/Clarity Test/images/salty/002_salty.png differ diff --git a/Clarity Test/images/salty/003_salty.jpg b/Clarity Test/images/salty/003_salty.jpg new file mode 100644 index 0000000..ba2c551 Binary files /dev/null and b/Clarity Test/images/salty/003_salty.jpg differ diff --git a/Clarity Test/images/salty/007_salty.png b/Clarity Test/images/salty/007_salty.png new file mode 100644 index 0000000..5b72026 Binary files /dev/null and b/Clarity Test/images/salty/007_salty.png differ diff --git a/Clarity Test/images/source/002.png b/Clarity Test/images/source/002.png new file mode 100644 index 0000000..20669eb Binary files /dev/null and b/Clarity Test/images/source/002.png differ diff --git a/Clarity Test/images/source/003.jpg b/Clarity Test/images/source/003.jpg new file mode 100644 index 0000000..76365e6 Binary files /dev/null and b/Clarity Test/images/source/003.jpg differ diff --git a/Clarity Test/images/source/007.png b/Clarity Test/images/source/007.png new file mode 100644 index 0000000..7f43b3d Binary files /dev/null and b/Clarity Test/images/source/007.png differ diff --git a/image_qualified.py b/datasets/image_qualified.py similarity index 88% rename from image_qualified.py rename to datasets/image_qualified.py index b624558..8452527 100644 --- a/image_qualified.py +++ b/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)