旋转目标检测复现-yolov5-obb

复现源码：
https://github.com/hukaixuan19970627/yolov5_obb
亲测可行
安装流程：
按照https://github.com/hukaixuan19970627/yolov5_obb/blob/master/docs/install.md
确保安装过程不报错，否则影响后续训练

安装成功即可准备数据集

hf_txt存放划分好的训练集、测试集、验证集，里面内容为数据图像文件名，
images存放要训练的图像
labelTxt存放将xml转换后的txt标签文件
hf.py数据集划分;

# -*- coding: utf-8 -*-
import os
import random
trainval_percent = 0.9
train_percent = 0.9
xmlfilepath = 'xml'
txtsavepath = 'images'
total_xml = os.listdir(xmlfilepath)
num = len(total_xml)
list = range(num)
tv = int(num * trainval_percent)
tr = int(tv * train_percent)
trainval = random.sample(list, tv)
train = random.sample(trainval, tr)
ftrainval = open('hf_txt/trainval.txt', 'w')
ftest = open('hf_txt/test.txt', 'w')
ftrain = open('hf_txt/train.txt', 'w')
fval = open('hf_txt/val.txt', 'w')
for i in list:name = total_xml[i][:-4] + '\n'if i in trainval:ftrainval.write(name)if i in train:ftrain.write(name)else:fval.write(name)else:ftest.write(name)
ftrainval.close()
ftrain.close()
fval.close()
ftest.close()

xml转txt；

# 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，转换成四点坐标x1,y1,x2,y2,x3,y3,x4,y4
import os
import xml.etree.ElementTree as ET
import mathdef edit_xml(xml_file,dotaxml_file):"""修改xml文件:param xml_file:xml文件的路径:return:"""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')xmin = float(obj_xmin.text)ymin = float(obj_ymin.text)xmax = float(obj_xmax.text)ymax = float(obj_ymax.text)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)for file in files:tree = ET.parse(xml_path + os.sep + file)root = tree.getroot()name = file.strip('.xml')output = out_path + name + '.txt'file = open(output, 'w')objs = 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))file.write("{} {} {} {} {} {} {} {} {} 0\n".format(x0, y0, x1, y1, x2, y2, x3, y3, cls))file.close()print(output)if __name__ == '__main__':# -----**** 第一步：把xml文件统一转换成旋转框的xml文件 ****-----roxml_path = "/root/autodl-tmp/yolov5_obb/dataset/dataset_demo/xml/"  # 目录下保存的是需要转换的xml文件dotaxml_path = '/root/autodl-tmp/yolov5_obb/dataset/dataset_demo/1xml/'out_path = '/root/autodl-tmp/yolov5_obb/dataset/dataset_demo/labelTxt/'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)

voc_label.py划分训练集，验证集，测试集路径：

# -*- coding: utf-8 -*-import xml.etree.ElementTree as ET
import os
from os import getcwdsets = ['train', 'val', 'test']
classes = ["large_car","small_car"]
abs_path = os.getcwd()wd = getcwd()
for image_set in sets:if not os.path.exists('labelTxt/'):os.makedirs('labelTxt/')image_ids = open('hf_txt/%s.txt' % (image_set)).read().strip().split()list_file = open('%s.txt' % (image_set), 'w')for image_id in image_ids:list_file.write(abs_path + '/images/%s.jpg\n' % (image_id))list_file.close()

修改相应数据集访问路劲

# Train/val/test sets as 1) dir: path/to/imgs, 2) file: path/to/imgs.txt, or 3) list: [path/to/imgs1, path/to/imgs2, ..]
#path: ./dataset # dataset root dir
train: dataset/dataset_demo/train.txt #images   # train images (relative to 'path')
val: dataset/dataset_demo/val.txt #images  # val images (relative to 'path')
#test: dataset_demo/images  #images # test images (optional)# Classes
nc: 2  # number of classes
names: ['large_car','small_car']  # class names# Download script/URL (optional)
# download: https://ultralytics.com/assets/coco128.zip

最后修改训练文件train.py,修改成对应的文件路径即可

上述都没问题即可训练

python train.py

扩展：部署yolov5-obb：
https://blog.csdn.net/qq_41043389/article/details/127777272

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