yolov5训练时出现“assertionerror:no labels found in */*/*/train2017.cache can not train without labels”

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yolov5训练时出现“assertionerror:no labels found in //*/train2017.cache can not train without labels”

yolov5训练时出现“assertionerror:no labels found in //*/train2017.cache can not train without labels”

傻了，label中的标签文件是xml格式，yolo v5要转成.txt格式

voc2txt.py

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

# 这里就体现出来了咱们在1.2步骤的时候我说的尽量按照那个目录名进行操作的优势，
# 在这可以剩下很多去修改名称的精力
# sets=[('2012', 'train'), ('2012', 'val'), ('2007', 'train'), ('2007', 'val'), ('2007', 'test')]
sets=[ ('2007', 'train'), ('2007', 'val'), ('2007', 'test')]  # 我只用了VOC2007

classes = ["ground-rod"]  # 修改为自己的label

def convert(size, box):
    dw = 1./(size[0]+0.1)  # 有的人运行这个脚本可能报错，说不能除以0什么的，你可以变成dw = 1./((size[0])+0.1)
    dh = 1./(size[1]+0.1)  # 有的人运行这个脚本可能报错，说不能除以0什么的，你可以变成dh = 1./((size[0])+0.1)
    x = (box[0] + box[1])/2.0 - 1
    y = (box[2] + box[3])/2.0 - 1
    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(year, image_id):
    in_file = open('VOCdevkit/VOC%s/Annotations/%s.xml'%(year, image_id),encoding='utf-8')
    out_file = open('VOCdevkit/VOC%s/labels/%s.txt'%(year, 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()

for year, image_set in sets:
    if not os.path.exists('VOCdevkit/VOC%s/labels/'%(year)):
        os.makedirs('VOCdevkit/VOC%s/labels/'%(year))
    image_ids = open('VOCdevkit/VOC%s/ImageSets/Main/%s.txt'%(year, image_set), encoding='utf-8').read().strip().split()
    list_file = open('%s_%s.txt'%(year, image_set), 'w', )
    for image_id in image_ids:
        list_file.write('%s/VOCdevkit/VOC%s/JPEGImages/%s.jpg\n'%(wd, year, image_id))
        convert_annotation(year, image_id)
    list_file.close()