目标检测旋转框格式转换

目标检测旋转框格式转换

文章目录

​​概要​​​​数据说明​​​​转换代码​​

概要

本篇博文将对目标检测旋转框格式转换做简单介绍，从带角度的旋转框转为四个角点的旋转框。

数据说明

转换代码

根据需求，需要将其转为四个角点的旋转框（x1, y1, x2, y2, x3, y3, x4, y4），并保存为txt格式。

import xml.etree.cElementTree as ETfrom xml.dom.minidom import Documentimport xml.dom.minidomimport numpy as npimport osimport mathimport sysimport globdef coordinate_convert_r(box): w, h = box[2:-1] theta = -box[-1] x_lu, y_lu = -w/2, h/2 x_ru, y_ru = w/2, h/2 x_ld, y_ld = -w/2, -h/2 x_rd, y_rd = w/2, -h/2 x_lu_ = math.cos(theta)*x_lu + math.sin(theta)*y_lu + box[0] y_lu_ = -math.sin(theta)*x_lu + math.cos(theta)*y_lu + box[1] x_ru_ = math.cos(theta) * x_ru + math.sin(theta) * y_ru + box[0] y_ru_ = -math.sin(theta) * x_ru + math.cos(theta) * y_ru + box[1] x_ld_ = math.cos(theta) * x_ld + math.sin(theta) * y_ld + box[0] y_ld_ = -math.sin(theta) * x_ld + math.cos(theta) * y_ld + box[1] x_rd_ = math.cos(theta) * x_rd + math.sin(theta) * y_rd + box[0] y_rd_ = -math.sin(theta) * x_rd + math.cos(theta) * y_rd + box[1] convert_box = [x_lu_, y_lu_, x_ru_, y_ru_, x_rd_, y_rd_, x_ld_, y_ld_] return convert_boxdef read_xml_gtbox_and_label(xml_path): """ :param xml_path: the path of voc xml :return: a list contains gtboxes and labels, shape is [num_of_gtboxes, 9], and has [x1, y1, x2, y2, x3, y3, x4, y4, label] in a per row """ tree = ET.parse(xml_path) root = tree.getroot() img_width = None img_height = None box_list = [] for child_of_root in root: if child_of_root.tag == 'Img_SizeWidth': img_width = int(child_of_root.text) if child_of_root.tag == 'Img_SizeHeight': img_height = int(child_of_root.text) if child_of_root.tag == 'HRSC_Objects': box_list = [] for child_item in child_of_root: if child_item.tag == 'HRSC_Object': label = 1 # for child_object in child_item: # if child_object.tag == 'Class_ID': # label = NAME_LABEL_MAP[child_object.text] tmp_box = [0., 0., 0., 0., 0.] for node in child_item: if node.tag == 'mbox_cx': tmp_box[0] = float(node.text) if node.tag == 'mbox_cy': tmp_box[1] = float(node.text) if node.tag == 'mbox_w': tmp_box[2] = float(node.text) if node.tag == 'mbox_h': tmp_box[3] = float(node.text) if node.tag == 'mbox_ang': tmp_box[4] = float(node.text) tmp_box = coordinate_convert_r(tmp_box) # assert label is not None, 'label is none, error' tmp_box.append(label) # if len(tmp_box) != 0: box_list.append(tmp_box) # box_list = coordinate_convert(box_list) # print(box_list) gtbox_label = np.array(box_list, dtype=np.int32) return img_height, img_width, gtbox_labeldef mkdir(path): if not os.path.exists(path): os.mkdir(path)if __name__ == '__main__': import matplotlib.pyplot as plt import cv2 as cv from shutil import copyfile src_image_path = './AllImages' src_xml_path = './Annotations' txt_path = './labelTxt' out_img_path = './images' mkdir(txt_path) mkdir(out_img_path) src_imgs = glob.glob(f'{src_image_path}/*.bmp') for img_path in src_imgs: try: ori_image = cv.imread(img_path) x_path = img_path[:-3].replace('AllImages', 'Annotations') + 'xml' img_height, img_width, gtbox_labels = read_xml_gtbox_and_label(x_path) if len(gtbox_labels) == 0: continue # for gtbox_label in gtbox_labels: # tl = np.asarray([gtbox_label[0], gtbox_label[1]], np.float32) # tr = np.asarray([gtbox_label[2], gtbox_label[3]], np.float32) # br = np.asarray([gtbox_label[4], gtbox_label[5]], np.float32) # bl = np.asarray([gtbox_label[6], gtbox_label[7]], np.float32) # box = np.asarray([bl, tl, tr, br], np.float32) # box = np.int0(box) # cv.drawContours(ori_image, [box], 0, (255, 255, 255), 1) # plt.imshow(ori_image) # plt.show() # print(gtbox_labels) name = os.path.split(img_path)[-1][:-4] for ann in gtbox_labels: with open(f"{txt_path}/{name}.txt", 'a+') as f: f.write(f"{ann[0]} {ann[1]} {ann[2]} {ann[3]} {ann[4]} {ann[5]} {ann[6]} {ann[7]} ship 0\n") cv.imwrite(f'{out_img_path}/{name}.png', ori_image) except: print(img_path)

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