SAR/test_data/xie/feature_hog.py

# import matplotlib.pyplot as plt
# from skimage.feature import hog
# from skimage import exposure, io
# import cv2
#
#
# def process_image(image_path):
#     # 读取图像
#     image = io.imread(image_path)
#
#     # 提取HOG特征
#     features, hog_image = hog(image, pixels_per_cell=(8, 8), cells_per_block=(2, 2), visualize=True)
#
#     # 对HOG图像进行对比度增强
#     hog_image_rescaled = exposure.rescale_intensity(hog_image, in_range=(0, 10))
#     #
#     # # 可视化结果
#     # plt.figure(figsize=(10, 5))
#     # plt.subplot(121)
#     # plt.imshow(image, cmap='gray')
#     # plt.title('Original Image')
#
#     plt.imshow(hog_image_rescaled, cmap='gray')
#     plt.title('HOG Image')
#     plt.savefig('path_to_save_image.png')
#
#     plt.show()
#
#
# # 在主程序中调用函数并传递图像路径
# if __name__ == "__main__":
#     import sys
#
#     if len(sys.argv) != 2:
#         sys.exit(1)
#
#     image_path = sys.argv[1]
#     process_image(image_path)
#

import matplotlib.pyplot as plt
from skimage.feature import hog
from skimage import exposure, io
import cv2
import os
import sys
plt.ioff()

def process_image(image_path):
    # 读取图像
    image = io.imread(image_path)

    # 提取HOG特征
    features, hog_image = hog(image, pixels_per_cell=(8, 8), cells_per_block=(2, 2), visualize=True)

    # 对HOG图像进行对比度增强
    hog_image_rescaled = exposure.rescale_intensity(hog_image, in_range=(0, 10))

    # 获取图像所在目录的文件夹名
    folder_name = os.path.basename(os.path.dirname(image_path))

    # 创建保存图像的文件夹
    save_folder = os.path.join(os.path.dirname(os.path.abspath(__file__)), 'hog', folder_name)
    os.makedirs(save_folder, exist_ok=True)

    # 保存图像
    save_path = os.path.join(save_folder, 'hog_' + os.path.basename(image_path))
    plt.imsave(save_path, hog_image_rescaled, cmap='gray')
    print(save_path)


# 在主程序中调用函数并传递图像路径
if __name__ == "__main__":

    if len(sys.argv) != 2:
        sys.exit(1)

    image_path = sys.argv[1]
    process_image(image_path)