记录yolov8_obb训练自己的数据集

# 文件名称   ：roxml_to_dota.py
# 功能描述   ：把rolabelimg标注的xml文件转换成dota能识别的xml文件，
#             再转换成dota格式的txt文件
#            把旋转框 cx,cy,w,h,angle，或者矩形框cx,cy,w,h,转换成四点坐标x1,y1,x2,y2,x3,y3,x4,y4
import os
import xml.etree.ElementTree as ET
import mathcls_list=['mouse']
def edit_xml(xml_file, dotaxml_file):"""修改xml文件:param xml_file:xml文件的路径:return:"""#dxml_file = open(xml_file,encoding='gbk')#tree = ET.parse(dxml_file).getroot()tree = ET.parse(xml_file)objs = tree.findall('object')for ix, obj in enumerate(objs):x0 = ET.Element("x0")  # 创建节点y0 = ET.Element("y0")x1 = ET.Element("x1")y1 = ET.Element("y1")x2 = ET.Element("x2")y2 = ET.Element("y2")x3 = ET.Element("x3")y3 = ET.Element("y3")# obj_type = obj.find('bndbox')# type = obj_type.text# print(xml_file)if (obj.find('robndbox') == None):obj_bnd = obj.find('bndbox')obj_xmin = obj_bnd.find('xmin')obj_ymin = obj_bnd.find('ymin')obj_xmax = obj_bnd.find('xmax')obj_ymax = obj_bnd.find('ymax')#以防有负值坐标xmin = max(float(obj_xmin.text),0)ymin = max(float(obj_ymin.text),0)xmax = max(float(obj_xmax.text),0)ymax = max(float(obj_ymax.text),0)obj_bnd.remove(obj_xmin)  # 删除节点obj_bnd.remove(obj_ymin)obj_bnd.remove(obj_xmax)obj_bnd.remove(obj_ymax)x0.text = str(xmin)y0.text = str(ymax)x1.text = str(xmax)y1.text = str(ymax)x2.text = str(xmax)y2.text = str(ymin)x3.text = str(xmin)y3.text = str(ymin)else:obj_bnd = obj.find('robndbox')obj_bnd.tag = 'bndbox'  # 修改节点名obj_cx = obj_bnd.find('cx')obj_cy = obj_bnd.find('cy')obj_w = obj_bnd.find('w')obj_h = obj_bnd.find('h')obj_angle = obj_bnd.find('angle')cx = float(obj_cx.text)cy = float(obj_cy.text)w = float(obj_w.text)h = float(obj_h.text)angle = float(obj_angle.text)obj_bnd.remove(obj_cx)  # 删除节点obj_bnd.remove(obj_cy)obj_bnd.remove(obj_w)obj_bnd.remove(obj_h)obj_bnd.remove(obj_angle)x0.text, y0.text = rotatePoint(cx, cy, cx - w / 2, cy - h / 2, -angle)x1.text, y1.text = rotatePoint(cx, cy, cx + w / 2, cy - h / 2, -angle)x2.text, y2.text = rotatePoint(cx, cy, cx + w / 2, cy + h / 2, -angle)x3.text, y3.text = rotatePoint(cx, cy, cx - w / 2, cy + h / 2, -angle)# obj.remove(obj_type)  # 删除节点obj_bnd.append(x0)  # 新增节点obj_bnd.append(y0)obj_bnd.append(x1)obj_bnd.append(y1)obj_bnd.append(x2)obj_bnd.append(y2)obj_bnd.append(x3)obj_bnd.append(y3)tree.write(dotaxml_file, method='xml', encoding='utf-8')  # 更新xml文件# 转换成四点坐标
def rotatePoint(xc, yc, xp, yp, theta):xoff = xp - xc;yoff = yp - yc;cosTheta = math.cos(theta)sinTheta = math.sin(theta)pResx = cosTheta * xoff + sinTheta * yoffpResy = - sinTheta * xoff + cosTheta * yoffreturn str(int(xc + pResx)), str(int(yc + pResy))def totxt(xml_path, out_path):# 想要生成的txt文件保存的路径，这里可以自己修改files = os.listdir(xml_path)i=0for file in files:tree = ET.parse(xml_path + os.sep + file)root = tree.getroot()name = file.split('.')[0]output = out_path +'\\'+name + '.txt'file = open(output, 'w')i=i+1objs = tree.findall('object')for obj in objs:cls = obj.find('name').textbox = obj.find('bndbox')x0 = int(float(box.find('x0').text))y0 = int(float(box.find('y0').text))x1 = int(float(box.find('x1').text))y1 = int(float(box.find('y1').text))x2 = int(float(box.find('x2').text))y2 = int(float(box.find('y2').text))x3 = int(float(box.find('x3').text))y3 = int(float(box.find('y3').text))if x0<0:x0=0if x1<0:x1=0if x2<0:x2=0if x3<0:x3=0if y0<0:y0=0if y1<0:y1=0if y2<0:y2=0if y3<0:y3=0for cls_index,cls_name in enumerate(cls_list):if cls==cls_name:file.write("{} {} {} {} {} {} {} {} {} {}\n".format(x0, y0, x1, y1, x2, y2, x3, y3, cls,cls_index))file.close()# print(output)print(i)if __name__ == '__main__':# -----**** 第一步：把xml文件统一转换成旋转框的xml文件 ****-----roxml_path = 'data_mouse_ro_1/org_xml' dotaxml_path = 'data_mouse_ro_1/dotaxml'  out_path = 'data_mouse_ro_1/dotatxt'   filelist = os.listdir(roxml_path)for file in filelist:edit_xml(os.path.join(roxml_path, file), os.path.join(dotaxml_path, file))# -----**** 第二步：把旋转框xml文件转换成txt格式 ****-----totxt(dotaxml_path, out_path)

sys.path.append('/path/to/ultralytics')
from ultralytics.data.converter import convert_dota_to_yolo_obb
convert_dota_to_yolo_obb('/home/fut/project/ultralytics-main/ultralytics/datasets_ro')

datasets--images--train--val--labelTxt--trian--val

import os
import random
import shutil# 设置随机数种子
random.seed(42)# 数据集文件夹路径和输出文件夹路径
data_folder = 'data_mouse_ro_1'
img_folder = 'data_mouse_ro_1/dataset/images'
label_folder = 'data_mouse_ro_1/dataset/labels'# 计算每个子集的大小
total_files = len(os.listdir(os.path.join(data_folder, 'img')))
train_size = int(total_files * 0.9)
test_size = int(total_files - train_size)# 获取所有图像文件的文件名列表
image_files = os.listdir(os.path.join(data_folder, 'img'))
random.shuffle(image_files)# 复制图像和标注文件到相应的子集文件夹中
for i, image_file in enumerate(image_files):base_file_name = os.path.splitext(image_file)[0]image_path = os.path.join(data_folder, 'img', image_file)label_path = os.path.join(data_folder, 'dotatxt', base_file_name + '.txt')if i < train_size:print(image_path)#print(os.path.join(img_folder, 'train'))shutil.copy(image_path, os.path.join(img_folder, 'train'))shutil.copy(label_path, os.path.join(label_folder, 'train_original'))else:shutil.copy(image_path, os.path.join(img_folder, 'val'))shutil.copy(label_path, os.path.join(label_folder, 'val_original'))

from ultralytics import YOLOdef main():model = YOLO('yolov8n-obb.yaml').load('yolov8n-obb.pt')  # build from YAML and transfer weightsmodel.train(data='dota8-obb.yaml', epochs=100, imgsz=640, batch=4, workers=4)
if __name__ == '__main__':main()