一、源码

直接去下载官方的yolov8源码就行，那里面集成了 obb

ultralytics/ultralytics/cfg/models/v8 at main · ultralytics/ultralytics · GitHub

二、环境

 如果你训练过yolov5以及以上的yolo环境，可以直接拷贝一个用就行，如果没有的话  直接pip

<code>pip install requirements.txt -i https://pypi.tuna.tsinghua.edu.cn/simple

可以配置cuda，跑的比较快

三、标注

标注方法有两种，一中是下载标注工具   X-Anylabeling

GitHub - CVHub520/X-AnyLabeling: Effortless data labeling with AI support from Segment Anything and other awesome models.

方法可以看我博客 

X-AnyLabeling标注软件安装及使用dota数据集，voc数据集，coco数据集。以及报错No module named‘anylabeling‘的解决_x-anylabeling-cpu 导出 dota 没数据-CSDN博客

不过上面那种标注方式我训练时总是报错 一直找不到原因，有知道的可以指教指教

另一种标注方式

用rolabelimg旋转标注软件 

GitHub - cgvict/roLabelImg: Label Rotated Rect On Images for training

      旋转标注工具roLabelImg使用教程-CSDN博客

配置完环境后 直接右键运行  roLabelImg.py文件

可以用旋转标注  标注后点击 标注的框   用  z,x,c,v  来更改 角度

生成的是xml文件

需要转换成dota能用的obb的txt文件

转换脚本

<code># 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 math

cls_list = ['angle'] # 修改为自己的标签

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')code>

# 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code>

# 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 * yoff

pResy = - sinTheta * xoff + cosTheta * yoff

return 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 = 0

for 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 + 1

objs = tree.findall('object')

for obj in objs:

cls = obj.find('name').text

box = 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 = 0

if x1 < 0:

x1 = 0

if x2 < 0:

x2 = 0

if x3 < 0:

x3 = 0

if y0 < 0:

y0 = 0

if y1 < 0:

y1 = 0

if y2 < 0:

y2 = 0

if y3 < 0:

y3 = 0

for 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 = r'H:\DL\YOLOv8_OBB_main\dataset_set\angle\1'

dotaxml_path = r'H:\DL\YOLOv8_OBB_main\dataset_set\angle\2'

out_path = r'H:\DL\YOLOv8_OBB_main\dataset_set\angle\4'

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)

转换后是如下的样子

但是这还没完，还需要再次转换一下

<code>from ultralytics import YOLO

model_yaml_path = r"H:\DL\YOLOv8_OBB_main\ultralytics\cfg\models\v8\yolov8-obb.yaml"

#数据集配置文件

data_yaml_path = 'data/hat.yaml'

#预训练模型

pre_model_name = 'yolov8s-obb.pt'

def main():

model = YOLO(model_yaml_path).load(pre_model_name) # build from YAML and transfer weights

model.train(data=data_yaml_path,

epochs=500,

imgsz=640,

batch=6,

workers=5,

name="train_obb/exp")code>

if __name__ == '__main__':

main()

# yolo obb train data=data/hat.yaml model=yolov8s-obb.pt epochs=200 imgsz=640 device=0

 detect.py 推理