WildfireDetection/datamange/xml2.py

"""
# File       : xml2.py
# Time       ：2024-04-04 12:16
# Author     ：FEANGYANG
# version    ：python 3.7
# Contact    ：1071082183@qq.com
# Description：
"""

import glob
import os
import cv2
import numpy as np


def read_xml(file):

    # actual parsing
    in_file = open(file)
    tree = ET.parse(in_file)
    root = tree.getroot()
    bboxes_list = []

    for obj in root.iter('object'):
        current = list()
        name = obj.find('name').text

        xmlbox = obj.find('bndbox')
        xn = xmlbox.find('xmin').text
        xx1 = xmlbox.find('xmax').text
        yn = xmlbox.find('ymin').text
        yx1 = xmlbox.find('ymax').text


        bboxes_list.append([xn, yn, xx1, yx1])

    return bboxes_list

def get_xmls_path_list(xmls_path):
    xmls_path_list = []

    for path in os.listdir(xmls_path):
        xml_path = '/'.join([xmls_path, path])
        xmls_path_list.append(xml_path)
        # bboxes_list = read_xml(xml_path)
    return xmls_path_list


def get_images_path_list(images_path):
    images_path_list = []

    for path in os.listdir(images_path):
        image_path = '/'.join([images_path, path])
        images_path_list.append(image_path)
    return  images_path_list



def test_xml2images_path(images_path, xmls_path_list):
    test_images_path_list = []
    test_xmls_path_list = []

    tmp_images_path = os.listdir(images_path)
    if len(tmp_images_path) > 3:
        suffex = os.path.splitext(tmp_images_path[2])[-1]
    else:
        raise ValueError('图片数量太少')

    for xml_path in xmls_path_list:
        xml_name = os.path.split(xml_path)[-1]
        image_path = '/'.join([images_path, os.path.splitext(xml_name)[0]+suffex])
        if os.path.exists(image_path):
            test_xmls_path_list.append(xml_path)
            test_images_path_list.append(image_path)

    return test_images_path_list, test_xmls_path_list


# def small_images(image_path, pixes,pic_target = './result/'):
#     if not os.path.exists(pic_target):  # 判断是否存在文件夹如果不存在则创建为文件夹
#         os.makedirs(pic_target)
#     picture = cv2.imread(image_path)
#     name = os.path.split(image_path)[-1]
#
#     (width, length, depth) = picture.shape
#     w, h, _ = picture.shape
#     # _w = w % pixes
#     # _h = h % pixes
#
#     cut_width = 64
#     cut_length = 64
#
#     # 预处理生成0矩阵
#     pic = np.zeros((cut_width, cut_length, depth))
#     # 计算可以划分的横纵的个数
#     num_width = int(width / cut_width)
#     num_length = int(length / cut_length)
#     # for循环迭代生成
#     lines_list = []
#     for i in range(0, num_width):
#         for j in range(0, num_length):
#             pic = picture[i * cut_width: (i + 1) * cut_width, j * cut_length: (j + 1) * cut_length, :]
#             result_path = pic_target + os.path.splitext(name)[0] +'_{}_{}.jpg'.format(i + 1, j + 1)
#             cv2.imwrite(result_path, pic)


def small_images(image_path, pixes,pic_target = './result/'):

    if not os.path.exists(pic_target):  # 判断是否存在文件夹如果不存在则创建为文件夹
        os.makedirs(pic_target)
    picture = cv2.imread(image_path)
    name = os.path.split(image_path)[-1]

    (length, width, depth) = picture.shape
    w, h, _ = picture.shape
    # _w = w % pixes
    # _h = h % pixes

    cut_width = 128
    cut_length = 128

    # 预处理生成0矩阵
    # pic = np.zeros((cut_width, cut_length, depth))
    # 计算可以划分的横纵的个数
    num_width = int(width / cut_width)

    num_length = int(length / cut_length)

    print(num_width, num_length)
    pixes += num_width * num_length
    print(pixes)
    # for循环迭代生成
    lines_list = []
    for i in range(0, num_width+1):
        lines_list.append([[i * cut_width, 0], [i * cut_width, w]])

    for j in range(0, num_length+1):
        lines_list.append([(0, j * cut_length), (h, j * cut_length)])

    point_color = (0, 0, 255)  # BGR
    thickness = 1
    lineType = 8

    for line in lines_list:
        cv2.line(picture, tuple(line[0]), tuple(line[1]), point_color, thickness, lineType)

    result_path = pic_target + os.path.splitext(name)[0] + '.jpg'

    cv2.imwrite(result_path, picture)

    return pixes


# def small_images(image_path, pixes, pic_target = './result/'):
#     if not os.path.exists(pic_target):  # 判断是否存在文件夹如果不存在则创建为文件夹
#         os.makedirs(pic_target)
#     crop_w = pixes  # 裁剪图像宽度
#     crop_h = pixes
#     img = cv2.imread(image_path)
#     name = os.path.split(image_path)[-1]
#     old_size = img.shape[0:2]  # 原图尺寸
#     # print(old_size[0],type(old_size[0]))
#     ######
#     if old_size[0] % crop_h != 0 and old_size[1] % crop_w != 0:
#
#         h_num = int(old_size[0] / crop_h) + 1  # 取整后加1
#         w_num = int(old_size[1] / crop_w) + 1
#
#         new_height = (h_num) * crop_h  # 小图像尺寸整倍数的大图像
#         new_width = (w_num) * crop_w
#         # print(new_height,new_width)
#         # #
#         pad_h = new_height - old_size[0]  # 计算自动需要填充的像素数目（图像的高这一维度上）
#         pad_w = new_width - old_size[1]  # 计算需要填充的像素数目（图像的宽这一维度上）
#         # print(pad_w,pad_h)
#
#         # top, bottom = pad_h // 2, pad_h - (pad_h // 2)
#         # left, right = pad_w // 2, pad_w - (pad_w // 2)
#         top, bottom = 0, pad_h
#         left, right = 0, pad_w
#         # print(top, bottom, left, right)
#         img_new = cv2.copyMakeBorder(img, top, bottom, left, right, cv2.BORDER_CONSTANT, None, (0, 0, 0))
#
#     else:
#         h_num = int(old_size[0] / crop_h)
#         w_num = int(old_size[1] / crop_w)
#         img_new = cv2.imread(image_path)
#
#     for i in range(h_num):
#         for j in range(w_num):
#             # print(i,j)
#             x = int(i * crop_h)  # 高度上裁剪图像个数
#             y = int(j * crop_w)
#             # print(x,y)
#             img_crop = img_new[x: x + crop_h, y: y + crop_w]
#             print(x, y, x + crop_h, y + crop_w)
#             # print(z)
#             saveName = os.path.splitext(name)[0] + '-' + str(i) + '-' + str(j) + ".png"  # 小图像名称，内含小图像的顺序
#             cv2.imwrite(pic_target + saveName, img_crop)



if __name__ == '__main__':
    images_path1 = './data/day_time_wildfire/images'
    xmls_path1 = './data/day_time_wildfire/annotations/xmls'

    images_path2 = './data/FlameVision/Detection/images'
    xmls_path2 = './data/FlameVision/Detection/annotations'

    images_path = images_path2
    xmls_path = xmls_path2

    xmls_path_list = get_xmls_path_list(xmls_path)
    images_path_list = get_images_path_list(images_path)

    # test_images_path_list, test_xmls_path_list = test_xml2images_path(images_path, xmls_path_list)
    sum = 0
    for image_path in images_path_list:

        sum = small_images(image_path, sum)





    pass