[YOLOV5]训练自己的数据集

import xml.etree.ElementTree as ET
import pickle
import os
from os import listdir, getcwd
from os.path import join

sets = ['train', 'test', 'val']
classes = ["yanwu", "fire"]

def convert(size, box):
dw = 1. / ((size[0]) + 0.1)
dh = 1. / ((size[0]) + 0.1)
x = (box[0] + box[1]) / 2.0
y = (box[2] + box[3]) / 2.0
w = box[1] - box[0]
h = box[3] - box[2]
x = x * dw
w = w * dw
y = y * dh
h = h * dh
return (x, y, w, h)

def convert_annotation(image_id):
in_file = open('VOC2007-1/Annotations/%s.xml' % (image_id))
out_file = open('VOC2007-1/labels/%s.txt' % (image_id), 'w')
tree = ET.parse(in_file)
root = tree.getroot()
size = root.find('size')
w = int(size.find('width').text)
h = int(size.find('height').text)
for obj in root.iter('object'):
difficult = obj.find('difficult').text
cls = obj.find('name').text
if cls not in classes or int(difficult) == 1:
continue
cls_id = classes.index(cls)
xmlbox = obj.find('bndbox')
b = (float(xmlbox.find('xmin').text), float(xmlbox.find('xmax').text), float(xmlbox.find('ymin').text),
float(xmlbox.find('ymax').text))
bb = convert((w, h), b)
out_file.write(str(cls_id) + " " + " ".join([str(a) for a in bb]) + '\n')

wd = getcwd()
print(wd)
for image_set in sets:
if not os.path.exists('VOC2007-1/labels/'):
os.makedirs('VOC2007-1/labels/')
image_ids = open('VOC2007-1/ImageSets/Main/%s.txt' % (image_set)).read().strip().split()
list_file = open('VOC2007-1/%s.txt' % (image_set), 'w')
for image_id in image_ids:
list_file.write('VOC2007-1/JPEGImages/%s.jpg\n' % (image_id))
convert_annotation(image_id)
list_file.close()

train: E:\yolo\yolov5_origin\VOC2007-1\test.txt
val: E:\yolo\yolov5_origin\VOC2007-1\val.txt
nc: 2
names: ["smoke","fire"]