我是训练的行人目标检测。

首先下载YOLOFastestv2：https://github.com/dog-qiuqiu/FastestDet

yolofastestv2需要这样的数据集：

python">.
├── category.names        # .names category label file
├── train                 # train dataset
│   ├── 000001.jpg
│   ├── 000001.txt
│   ├── 000002.jpg
│   ├── 000002.txt
│   ├── 000003.jpg
│   └── 000003.txt
├── train.txt              # train dataset path .txt file
├── val                    # val dataset
│   ├── 000043.jpg
│   ├── 000043.txt
│   ├── 000057.jpg
│   ├── 000057.txt
│   ├── 000070.jpg
│   └── 000070.txt
└── val.txt                # val dataset path .txt file

一般我们的数据集是voc样式的数据集即文件夹中只有这两个文件：

train和val文件夹内的0001.txt为yolo数据集的格式，其内容如下：

python">0 0.344192634561 0.611 0.416430594901 0.262
1 0.509915014164 0.51 0.974504249292 0.972

首先我们将xml转成这个格式的，在Annotations和JPEGImages的同级路径下创建一个py文件：

python"># 作者：李富贵
# 公众号：猛男技术控
# 输入：xml的文件夹路径
# 输出：在txt路径下创建对应的txt文件
import xml.etree.ElementTree as ET
import os

def convert(size, box):
    dw = 1. / (size[0])
    dh = 1. / (size[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(xml_file, txt_path, filename):
    in_file = open('{}/{}.xml'.format(xml_file, filename), encoding='UTF-8')
    out_file = open('{}/{}.txt'.format(txt_path, filename), '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
        # difficult = obj.find('Difficult').text
        if obj.find('difficult'):
            difficult = obj.find('difficult').text
        else:
            difficult = 0
        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))
        b1, b2, b3, b4 = b
        # 标注越界修正
        if b2 > w:
            b2 = w
        if b4 > h:
            b4 = h
        b = (b1, b2, b3, b4)
        bb = convert((w, h), b)
        out_file.write(str(cls_id) + " " + " ".join([str(a) for a in bb]) + '\n')


# 改成自己的类别
classes = ["person"]
# 改成自己xml文件夹和要保存的txt文件夹的路径
xml_path = 'Annotations'
txt_path = 'txt'
if not os.path.exists(txt_path):
    os.makedirs(txt_path)

xml_files = os.listdir(xml_path)
for xml_file in xml_files:
    print(xml_path + '/' + xml_file)
    convert_annotation(xml_path, txt_path, xml_file[:-4])
    

然后得到一个txt文件，里面就是存放所有已转换的txt

第二步就是将文件分成train和test

python">import os
import shutil
import random

all_txt = os.listdir('txt')
random.shuffle(all_txt)


trainf = all_txt[:1316]
vlaf = all_txt[1317:]

i = 1
for trainimg in trainf:
    try:
        shutil.copy(os.path.join('JPEGImages',trainimg[:-3]+'png'),'train')
        shutil.copy(os.path.join('txt', trainimg), 'train')
        print(i)
        i += 1
    except:
        print('no such file ',os.path.join('JPEGImages',trainimg[:-3]+'jpg'))
j = 1

for valimg in vlaf:
    try:
        shutil.copy(os.path.join('JPEGImages',valimg[:-3]+'png'),'v')
        shutil.copy(os.path.join('txt', valimg), 'v')
        print(j)
        j += 1

    except:
        print('no such file ',os.path.join('JPEGImages',valimg))

注意自己创建号train和val文件夹，修改train和val文件的个数。
这样就生成了下面这样的文件

python">├── train
│   ├── 000001.jpg
│   ├── 000001.txt
│   ├── 000002.jpg
│   ├── 000002.txt
│   ├── 000003.jpg
│   └── 000003.txt
└── val
    ├── 000043.jpg
    ├── 000043.txt
    ├── 000057.jpg
    ├── 000057.txt
    ├── 000070.jpg
    └── 000070.txt

然后将所有文件读入txt中：

python">import os

traintxt = open('train.txt','a')
val = open('val.txt','a')
for img in os.listdir('train'):
    if "png" in img:
        traintxt.write(os.path.join('INRIAPerson-823/train',img)+'\n')
        print(img)

    else:
        print(img,'error')
for img in os.listdir('val'):
    if "png" in img:
        valtxt.write(os.path.join('INRIAPerson-823/val',img)+'\n')
        print(img)
    else:
        print(img,'error')
valtxt.close()
traintxt.close()

然后修改data下的.data文件

对应的路径自己修改

然后就是训练了：
先跑下这个：

python">python3 genanchors.py --traintxt ./train.txt

然后

python">python3 train.py --data data/coco.data

下不了的关注我公众号：猛男技术控，回复yolofastest 可以提供代码、数据、以及我训练的权重。