【深度学习】darknet训练分类

最新推荐文章于 2023-10-24 17:10:28 发布

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最新推荐文章于 2023-10-24 17:10:28 发布

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文章标签：人工智能 c/c++

原文链接：https://my.oschina.net/KFS/blog/3029221

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本文介绍如何使用Darknet进行目标分类训练，包括配置文件详解及常见问题解决方法。

摘要生成于 C知道，由 DeepSeek-R1 满血版支持，前往体验 >

为什么80%的码农都做不了架构师？>>>

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);
}