【深度学习】darknet训练分类

柔情只为你懂 2022-01-17 00:05 582阅读 0赞

[为什么80%的码农都做不了架构师？>>> ][80_]  ![hot3.png][]

> **首先感谢`AlexeyAB`大神的`darknet`版本**

*  下载编译就不说了简单说下训练。
 *  首先在目录找到cfg/darknet19.cfg

[net]
    # Training
    #batch=128
    #subdivisions=2
    
    # Testing
     batch=1
     subdivisions=1
    
    height=256
    width=256
    min_crop=128
    max_crop=448
    channels=3
    momentum=0.9
    decay=0.0005
    
    burn_in=1000
    learning_rate=0.1
    policy=poly
    power=4
    max_batches=800000
    
    angle=7
    hue=.1
    saturation=.75
    exposure=.75
    aspect=.75
    
    [convolutional]
    batch_normalize=1
    filters=32
    size=3
    stride=1
    pad=1
    activation=leaky
    
    [maxpool]
    size=2
    stride=2
    
    [convolutional]
    batch_normalize=1
    filters=64
    size=3
    stride=1
    pad=1
    activation=leaky
    
    [maxpool]
    size=2
    stride=2
    
    [convolutional]
    batch_normalize=1
    filters=128
    size=3
    stride=1
    pad=1
    activation=leaky
    
    [convolutional]
    batch_normalize=1
    filters=64
    size=1
    stride=1
    pad=1
    activation=leaky
    
    [convolutional]
    batch_normalize=1
    filters=128
    size=3
    stride=1
    pad=1
    activation=leaky
    
    [maxpool]
    size=2
    stride=2
    
    [convolutional]
    batch_normalize=1
    filters=256
    size=3
    stride=1
    pad=1
    activation=leaky
    
    [convolutional]
    batch_normalize=1
    filters=128
    size=1
    stride=1
    pad=1
    activation=leaky
    
    [convolutional]
    batch_normalize=1
    filters=256
    size=3
    stride=1
    pad=1
    activation=leaky
    
    [maxpool]
    size=2
    stride=2
    
    [convolutional]
    batch_normalize=1
    filters=512
    size=3
    stride=1
    pad=1
    activation=leaky
    
    [convolutional]
    batch_normalize=1
    filters=256
    size=1
    stride=1
    pad=1
    activation=leaky
    
    [convolutional]
    batch_normalize=1
    filters=512
    size=3
    stride=1
    pad=1
    activation=leaky
    
    [convolutional]
    batch_normalize=1
    filters=256
    size=1
    stride=1
    pad=1
    activation=leaky
    
    [convolutional]
    batch_normalize=1
    filters=512
    size=3
    stride=1
    pad=1
    activation=leaky
    
    [maxpool]
    size=2
    stride=2
    
    [convolutional]
    batch_normalize=1
    filters=1024
    size=3
    stride=1
    pad=1
    activation=leaky
    
    [convolutional]
    batch_normalize=1
    filters=512
    size=1
    stride=1
    pad=1
    activation=leaky
    
    [convolutional]
    batch_normalize=1
    filters=1024
    size=3
    stride=1
    pad=1
    activation=leaky
    
    [convolutional]
    batch_normalize=1
    filters=512
    size=1
    stride=1
    pad=1
    activation=leaky
    
    [convolutional]
    batch_normalize=1
    filters=1024
    size=3
    stride=1
    pad=1
    activation=leaky
    
    [convolutional]
    filters=1000
    size=1
    stride=1
    pad=1
    activation=linear
    
    [avgpool]
    
    [softmax]
    groups=1

*  样本就是 类别\_随机数.png 也可以 随机数\_类别.png
 *  网上很多人博客说什么不要在路径出现多个或者无类别的单词，很多人照猫画虎不解其意实际上我们打开源码根据错误定位到这个函数

void fill_truth(char *path, char **labels, int k, float *truth)
    {
        int i;
        memset(truth, 0, k*sizeof(float));
        int count = 0;
        for(i = 0; i < k; ++i){
            if(strstr(path, labels[i])){
                truth[i] = 1;
                ++count;
                //printf("%s %s %d\n", path, labels[i], i);
            }
        }
        if(count != 1 && (k != 1 || count != 0)) printf("Too many or too few labels: %d, %s\n", count, path);
    }

*  路径和类别strstr判断的 所以我们可以知道只要路径上只需要一个类别字符就可以了。甚至可以每个样本放在每个文件夹也是可以的
 *  编译的时候会有些小问题，这个版本的darknet貌似为了rpc 加了一些c++的代码可以把那几个cpp删掉依赖也注释就行了实际上用不到的
 *  搞定这个就可以愉快的训练了，有作者提供的darknet系列分类网络或者res系列的就可以训练分类器了。
 *  具体配置网上一大堆，盘他就对了

转载于:https://my.oschina.net/KFS/blog/3029221

[80_]: https://my.oschina.net/u/2663968/blog/3051541
[hot3.png]: /images/20220117/551eb446e88745eea453f42f9e0612b2.png