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  • ImageFeatures

    2018-10-11 22:41:55
    struct CV_EXPORTS ImageFeatures { int img_idx; Size img_size; std::vector keypoints; Mat descriptors; };

    struct CV_EXPORTS ImageFeatures
    {
    int img_idx;
    Size img_size;
    std::vector keypoints;
    Mat descriptors;
    };

    展开全文
  • Extracting Features

    2017-01-09 17:33:16
    Extracting Features In this tutorial, we will extract features using a pre-trained model with the included C++ utility. Note that we recommend using the Python interface for this task, as for examp

    Extracting Features

    In this tutorial, we will extract features using a pre-trained model with the included C++ utility. Note that we recommend using the Python interface for this task, as for example in the filter visualization example.

    Follow instructions for installing Caffe and run scripts/download_model_binary.py models/bvlc_reference_caffenet from caffe root directory. If you need detailed information about the tools below, please consult their source code, in which additional documentation is usually provided.

    Select data to run on

    We’ll make a temporary folder to store things into.

    mkdir examples/_temp
    

    Generate a list of the files to process. We’re going to use the images that ship with caffe.

    find `pwd`/examples/images -type f -exec echo {} \; > examples/_temp/temp.txt
    

    The ImageDataLayer we’ll use expects labels after each filenames, so let’s add a 0 to the end of each line

    sed "s/$/ 0/" examples/_temp/temp.txt > examples/_temp/file_list.txt
    

    Define the Feature Extraction Network Architecture

    In practice, subtracting the mean image from a dataset significantly improves classification accuracies. Download the mean image of the ILSVRC dataset.

    ./data/ilsvrc12/get_ilsvrc_aux.sh
    

    We will use data/ilsvrc212/imagenet_mean.binaryproto in the network definition prototxt.

    Let’s copy and modify the network definition. We’ll be using the ImageDataLayer, which will load and resize images for us.

    cp examples/feature_extraction/imagenet_val.prototxt examples/_temp
    

    Extract Features

    Now everything necessary is in place.

    ./build/tools/extract_features.bin models/bvlc_reference_caffenet/bvlc_reference_caffenet.caffemodel examples/_temp/imagenet_val.prototxt fc7 examples/_temp/features 10 leveldb
    

    The name of feature blob that you extract is fc7, which represents the highest level feature of the reference model. We can use any other layer, as well, such as conv5 or pool3.

    The last parameter above is the number of data mini-batches.

    The features are stored to LevelDB examples/_temp/features, ready for access by some other code.

    If you meet with the error “Check failed: status.ok() Failed to open leveldb examples/_temp/features”, it is because the directory examples/_temp/features has been created the last time you run the command. Remove it and run again.

    rm -rf examples/_temp/features/
    

    If you’d like to use the Python wrapper for extracting features, check out the filter visualization notebook.

    Clean Up

    Let’s remove the temporary directory now.

    rm -r examples/_temp
    展开全文
  • SLAM Features detection/Description

    万次阅读 2019-12-14 12:37:28
    Features Features detection/Description From handcrafted to deep local features. G. Csurka, C. R. Dance, M. Humenberger. 2018. Project Detection Description AKAZE x MSURF/MLDB DART x x KAZ...

    Features

    Features detection/Description

    From handcrafted to deep local features. G. Csurka, C. R. Dance, M. Humenberger. 2018.

    Project Detection Description
    AKAZE x MSURF/MLDB
    DART x x
    KAZE x MSURF/MLDB
    LIOP/MIOP x
    LIFT (machine learning) x x
    MROGH x
    SIFT x x
    SURF x x
    SFOP x
    展开全文
  • bs4.FeatureNotFound: Couldn't find a tree builder with the features you requested: lxml. Do you need to install a parser library? 几经周折才知道是bs4调用了python自带的html解析器,我用的mac,默认安装的...

    Python小白,学习时候用到bs4解析网站,报错

    bs4.FeatureNotFound: Couldn't find a tree builder with the features you requested: lxml. Do you need to install a parser library?

    几经周折才知道是bs4调用了python自带的html解析器,我用的mac,默认安装的是python2,所以内置的解释器也是捆绑在python2上,而我学习的时候又自己安装了python3,开发环境也是python3的,貌似是没有html解释器,所以会报错。
    问题找到了,那么怎么解决呢?对,在python3也装一个html解析器就好了,那么怎么安装呢?查阅资料获悉:一般pip和pip2对应的是python2.x,pip3对应的是python3.x的版本,python2和python3的模块是独立的,不能混用,混用会出问题。所以命令行通过python3的pip:pip3 安装解析器:

    $ pip3 install lxml

    3.8M,稍等片刻即可
    再次运行项目,完美解决,特此记录

    说的直白点就是你的开发环境下下载的包里不存在你需要的lxml,比如说你用的是py2,但是把包装到了py3的包路径下,当然就找不到了,反之亦然。那么就检查一下当前的开发环境是用的Python版本和对应的Python版本下的Packages目录下有没有你需要的包,如果没有就安装一个。就是这么简单。

    $ pip3(如果是py2就用pip) show lxml

    如果已经安装了就会显示包的位置及信息,没有则会报错,执行上一步安装操作即可

    展开全文
  • 编译一个项目报错如下: CMake Error at Rx/v2/test/CMakeLists.txt:125 (target... target_compile_features no known features for CXX compiler "" version . 经过调查,可能是由于target_compile_features ...
  • Python Hidden Features

    2016-05-21 22:20:49
    python hidden features
  • Tensorfow里的Features(tf.train.Features

    千次阅读 2019-03-01 13:47:32
    Features是用于描述机器学习模型训练或推理的特征的协议消息,用键值对表示数据。 Feature有三种形式: - bytes - float - int64 一个Features中包括可能包含零个或多个值的列表。 这些列表是基本值BytesList,...
  • Spring Boot features

    2019-04-17 21:41:34
    https://docs.spring.io/spring-boot/docs/current/reference/html/boot-features-spring-application.html 此篇文章主要介绍了SpringBoot的主要功能: 1.通常通过SpringApplication.run方法启动; 2.SpringBoot有...
  • Haralick texture features

    千次阅读 2018-04-01 10:18:05
    Haralick texture featuresHaralick's texture features [28] were calculated using the kharalick() function of the cytometry tool box [29] for Khoros (version 2.1 Pro, Khoral Research, Inc., ...
  • GBDT对max_features调参时 ‘max_features’:range(7,20,2) 会遇到: ValueError: max_features must be in (0, n_features] 是因为: If float, then max_features is a percentage and int(max_features * n_...
  • Android NDK CPU Features detection library: ----------------------------------------------------------- NDK 提供了一个很小的库叫着“cpufeatures”,可用于运行时检测目标设备的CPU类型和它...
  • cpufeatures

    2012-05-26 19:46:17
    the source is in /media/LENOVO/src1/1/android-20120108-2.2.2_r1/ndk/sources/cpufeatures. http://blog.csdn.net/abnerchai/article/details/6830644
  • matlab中extractFeatures函数的用法

    千次阅读 2020-02-09 22:00:40
    matlab中extractFeatures函数的用法公式描述输入参数输出参数 公式 [features,validPoints] = extractFeatures(I,points) [features,validPoints] = extractFeatures(I,points,Name,Value) 描述 [features,...
  • PolynomialFeatures多项式转换

    千次阅读 2018-12-05 22:36:55
    使用sklearn.preprocessing.PolynomialFeatures来进行特征的构造。 它是使用多项式的方法来进行的,如果有a,b两个特征,那么它的2次多项式为(1,a,b,a^2,ab, b^2)。 PolynomialFeatures有三个参数 degree:控制...
  • Bag of features

    2016-07-06 10:14:47
    Bag of features http://blog.csdn.net/royalvane/article/details/6649068 http://baike.sogou.com/v73026138.htm?fromTitle=tf-idf
  • sklearn preprocessing PolynomialFeatures 用法
  • torch.nn.Linear(in_features, out_features, bias=True)[source] Applies a linear transformation to the incoming data: Parameters in_features – size of each input sample out_features – size ...
  • in_features--每个输入样本的大小 out_features--每个输出样本的大小 bias--如果设置为False,则图层不会学习附件偏差,默认值:True import torch.nn as nn import torch m = nn.Linear(20, 30) input = torch....
  • 介绍python_speech_features模块 python_speech_features.mfcc() -梅尔频率倒谱系数 python_speech_features.fbank() -滤波器能量 python_speech_features.logfbank() -Log Filterbank能量 python_speech_features....
  • 之前的文章介绍了Numerical features,今天来介绍Categorical features。Categorical features 在我们的生活中也很常见,小到一年四季,一周七天,色彩颜色种类;大到用户id,CTR中的广告对象,这些都是属于...
  • NDK CPU Features

    千次阅读 2013-04-02 13:11:11
    Android NDK CPU Features detection library: ------------------------------------------- This NDK provides a small library named "cpufeatures" that can be used at runtime to detect the target device's
  • This example shows how to do clustering on point features. 这个例子用来展示如何对点要素尽心聚合。 代码: Clustered Features cluster distance
  • Learning Deep Features for Discriminative Localization论文笔记以及Caffe实现论文笔记 | Learning Deep Features for Discriminative Localization论文笔记: Learning Deep Features for Discriminative ...
  • 发布karaf的features

    千次阅读 2014-08-02 15:34:30
    Karaf的features是其本身的一大亮点,通过features可以完成某个功能相关bundle的安装和卸载,极大的方便了对bundle的管理。 Karaf的最新版本是2.3.2,通过features:install 命令,安装的features都是在data目录下...
  • android dynamic features 项目笔记

    千次阅读 2019-02-20 16:56:02
    android dynamic features 项目笔记 第一步(创建项目) 创建Instant Dynamic Feature Module File -> New Module -> Instant Dynamic Feature Module Finish 构建项目 第二步(创建页面) 我们在...
  • 170712 python_speech_features

    千次阅读 2017-07-12 12:08:00
    Welcome to python_speech_features’s documentation! Audio tools for Linux commandline geeks Code:from python_speech_features import mfcc from python_speech_features import logfbank import scipy.io....
  • librosa与python_speech_features

    千次阅读 2019-11-03 11:14:46
    在语音识别领域,比较常用的两个模块就是librosa和python_speech_features了。直接对比两文档就可以看出librosa功能十分强大,涉及到了音频的特征提取、谱图分解、谱图显示、顺序建模、创建音频等功能,而python_...
  • cs231n assignment1 features

    2019-07-17 17:25:28
    features 前几个作业都是直接将图片的原始像素作为模型输入,本次作业是通过使用定向梯度直方图Histogram of Oriented Gradients (HOG)和HSV颜色空间。简单说,HOG不考虑图片的颜色信息,只捕获图片的纹理;而颜色...

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