caffe

TensorFlow 人工智能引擎 入门教程之一 基本概念以及理解

由 ◇◆丶佛笑我妖孽 提交于 2019-12-23 20:04:23
【推荐】2019 Java 开发者跳槽指南.pdf(吐血整理) >>> 首先大家看2 张图片 在0.8版本时候已经支持分布式了 ，所以未来的发展 方面 人工智能的趋势 不可挡，而且个人也是非常喜欢caffe 以及 tensorFlow 的我创业 用的就用到了它。 下面我们来讲一下 学习tensorFlow要了解的基础知识。 首先安装方面 很简单 ubuntu 下 pip install 这里 知识安装普通的0.5版本，如果需要最新版 看github上最新的0.8版本 安装好了 就可以开始使用了 首先 1.tensorflow = tensor + flow = ndarray + dag图(网络) 也就是说 通过 每一个 有向图 dag 把每一步操作op 连接起来 传递 输入 输出都是一个nd array 多维数组(numpy) 然后在tensorFlow的回话中进行计算操作， 1.占位符 x = tf.placeholder(tf.float32, [None, 10]) y = tf.placeholder("float") z = tf.placeholder(tf.int32) 占位符表示当OP 操作进行时候传递进来的过程,,也就是 feed 喂养 给予操作，所以 需要外部传递过来，比如训练图像时候 X 为图像数据 Y为图像标签，这样的时候 X Y 都是来自训练测试数据

Writing Custom Python Layer With Learnable Parameters in Caffe

由 人走茶凉 提交于 2019-12-23 16:43:16
问题 I know that this example is supposed to illustrate how to add trainable parameters in a Python layer using the add_blob() method. However, I am still unable to understand how this can be used to set the dimensions of the blob based on user defined parameters. There is a better example here on how to write a Python layer here. But here, the layer does not contain any trainable parameters. Please explain how to write a custom Python layer with trainable parameters. 回答1: When you add a

Labels in Caffe as Images

由 萝らか妹 提交于 2019-12-23 12:31:44
问题 I'm new to Caffe. I am trying to implement a Fully Convolution Neural Network (FCN-8s) for semantic segmentation. I have image data and label data, which are both images. This is for pixel-wise predictions. I tried using ImageData as the data type, but it asks for an integer label, which is not applicable to this scenario. Kindly advise as how to I can give Caffe a 2D label. Should I prefer LMDB instead of ImageData? If so, how do I proceed? I could not find any good tutorial/documentation

ubuntu安装caffe

由 爱⌒轻易说出口 提交于 2019-12-23 10:00:51
安装依赖 sudo apt-get install libprotobuf-dev libleveldb-dev libsnappy-dev libopencv-dev sudo apt-get install libhdf5-serial-dev protobuf-compiler sudo apt-get install --no-install-recommends libboost-all-dev sudo apt-get install libopenblas-dev liblapack-dev libatlas-base-dev sudo apt-get install libgflags-dev libgoogle-glog-dev liblmdb-dev 解压 wget https://github.com/BVLC/caffe/archive/1.0.tar.gz . tar -vxzf 1.0.tar.gz 复制makefile.conf文件 sudo gedit Makefile.config 将第5行注释去掉 USE_CUDNN := 1 将第21行注释 OPENCV_VERSION := 3 将第37和38行删除（cuda8.0后不再支持），也就是删 除-gencode arch=compute_20,code=sm_20 \和-gencode arch

RMSprop, Adam, AdaDelta test accuracy does not improve using Caffe

由 左心房为你撑大大i 提交于 2019-12-23 09:38:04
问题 I am finetuning using Caffe on an image dataset on a Tesla K40 . Using a batch size=47 , solver_type=SGD , base_lr=0.001 , lr_policy="step" , momentum=0.9 , gamma=0.1 , the training loss decreases and test accuracy goes from 2%-50% in 100 iterations which is quite good. When using other optimisers such as RMSPROP , ADAM and ADADELTA , the training loss remains almost the same even and no improvement in test accuracy after 1000 iterations. For RMSPROP , I have changed the respective parameters

Install Caffe on Mac error: “fatal error: 'cblas.h' file not found”

由 痞子三分冷 提交于 2019-12-23 08:59:37
问题 I've been following this guide to install on my El Capitan macbook pro, using CMake to build the makefile. However, when I attempt to make, I run into the error of missing the cblas.h file. I successfully reinstalled openblas with: $ brew uninstall openblas; brew install --fresh -vd openblas and adding the two build flags: LDFLAGS: -L/usr/local/opt/openblas/lib CPPFLAGS: -I/usr/local/opt/openblas/include However I still get the error. Then I reinstalled CUDA and xcode-select install tools as

caffe和pytorch如何从文件file和流stream中导入模型？| load model from file and stream for caffe and pytorch

由 我们两清 提交于 2019-12-23 08:19:03
【推荐】2019 Java 开发者跳槽指南.pdf(吐血整理) >>> 本文首发于个人博客 https://kezunlin.me/post/5898412/ ，欢迎阅读最新内容！ load model from file and stream for caffe and pytorch <!--more--> Guide caffe load from file enum caffe::Phase phase = caffe::Phase::TEST; std::string proto_filepath = "yolov3.prototxt"; std::string weight_filepath = "yolov3.caffemodel"; caffe::Net<float> net = caffe::Net<float>(proto_filepath, phase)); net.CopyTrainedLayersFrom(weight_filepath); load from stream no caffe method to load directly from stream. we can override ReadProtoFromTextFile and ReadProtoFromBinaryFile in src/caffe/util/io.cpp to

make pycaffe fatal error: 'Python.h' file not found

由 纵然是瞬间 提交于 2019-12-23 07:38:51
问题 I compiled caffe on a mac running OSX 10.9.5 and I know trying to compile pycaffe. When I run make pycaffe in the caffe root folder, I get: CXX/LD -o python/caffe/_caffe.so python/caffe/_caffe.cpp python/caffe/_caffe.cpp:1:10: fatal error: 'Python.h' file not found #include <Python.h> // NOLINT(build/include_alpha) ^ 1 error generated. make: *** [python/caffe/_caffe.so] Error 1 how can I fix this? Perhaps is something wrong with Makefile.config. How do I know what is my PYTHONPATH? 回答1:

Conda command fails silently

由 北战南征 提交于 2019-12-23 07:06:44
问题 My anaconda is behaving oddly. conda list , conda debug , conda install , all return nothing . I have already reinstalled anaconda2 , checked my path on .profile , and it's all there. 1. which -a conda /Users/me/anaconda2/bin/conda 2. echo $PATH /Users/me/anaconda2/bin:/usr/local/bin:/usr/bin:/bin:/usr/sbin:/sbin:/opt/X11/bin:/usr/local/MacGPG2/bin 3. ~/.profile : # added by Anaconda2 5.0.1 installer export PATH="/Users/me/anaconda2/bin:$PATH" 4. brew doctor : Warning: "config" scripts exist

Food101 SqueezeNet Caffe2 number of iterations

由 老子叫甜甜 提交于 2019-12-23 05:05:07
问题 I am trying to classify the ETH Food-101 dataset using squeezenet in Caffe2. My model is imported from the Model Zoo and I made two types of modifications to the model: 1) Changing the dimensions of the last layer to have 101 outputs 2) The images from the database are in NHWC form and I just flipped the dimensions of the weights to match. (I plan on changing this) The Food101 dataset has 75,000 images for training and I am currently using a batch size of 128 and a starting learning rate of
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