caffe2

FAIR-Detectron 开源代码

我的未来我决定 提交于 2021-02-15 02:26:32
先贴上链接:https://github.com/facebookresearch/Detectron 。。。Install Caffe2 就问题一大堆了。。。。 首先是下载完caffe2工程后,第一步的make ,就出现“Protocol "https" not supported or disabled in libcurl” 试了很多方法,都不管用,哎。 应该是curl的问题,不管了,反正系统已经重装了,现在一切正常,比以前还顺溜~ 装个这玩意让我火大。直接重装系统!!!!! 全新的系统:Ubuntu14.04!!! 显卡:GTX 1080 本以为重装系统的话,cuda这玩意又要倒腾很久,已经做好了长期奋战的准备,结果 - - 时代在进步啊,要是当年有这么好装的话,我也不用装大半个月了。 废话不多说,总结下今天安装 caffe2 的过程。 一、 首先下载依赖项: sudo apt- get update sudo apt-get install -y --no- install - recommends \ build - essential \ cmake \ git \ libgoogle -glog- dev \ libgtest - dev \ libiomp - dev \ libleveldb - dev \ liblmdb - dev \ libopencv -

windows下用c++调用caffe做前向

偶尔善良 提交于 2021-02-11 13:10:42
参考博客: https://blog.csdn.net/muyouhang/article/details/54773265 https://blog.csdn.net/hhh0209/article/details/79830988 新建caffe的属性表,caffe_gpu_x64_release.props 将NugetPackages,caffe,CUDA中的头文件加进去 属性-C/C++-附加包含目录: D:\caffe20190311\NugetPackages\OpenCV.2.4.10 \build\native\include D:\caffe20190311\NugetPackages\OpenBLAS. 0.2.14.1 \lib\native\include D:\caffe20190311\NugetPackages\protobuf -v120.2.6.1 \build\native\include D:\caffe20190311\NugetPackages\glog. 0.3.3.0 \build\native\include D:\caffe20190311\NugetPackages\gflags. 2.1.2.1 \build\native\include D:\caffe20190311\NugetPackages\boost. 1.59.0

小白离线快速安装GPU版pytorch(不用镜像源,解决安装缓慢问题)

风格不统一 提交于 2020-08-12 08:53:03
近期,安装pytorch入了很多坑,清华的镜像源不能用,这就很烦人了。我尝试了很多种,中科大源也尝试了,但是 还是不行。后来呢,我就去尝试离线安装,最开始在清华的镜像网下载的离线安装包,用conda命令安装后出现了caffe2_detectron_ops_gpu.dll模块加载不了或者缺少依赖项。(这个问题我查了1整天,见到过几个这个问题,但是由于人家用的是Mac的系统,我就更难受了)最后,我去官网下载的对应版本的离线安装包,然后就安装成功了。(忒棒嘞)详细步骤如下: 1、在安装GPU版本pytorch之前先安装对应版本的CUDA和CUDNN (详细安装见我的CUDA和CUDNN的安装文章 https://blog.csdn.net/wobushizhainanyu/article/details/107736090 ) 2、去pytorch官网找到对应要安装的版本 https://pytorch.org/ 复制对应版本的后边的那个链接,浏览器打开 3、打开上述链接后找到对应版本的包下载torch和torchvision版本需要对应,例如我的 4、然后打开命令行 cd切换目录至上述两个包所下载的位置 然后pip安装就可以 5、验证pytorch安装成功,输入下图命令,如下图的话就成功了 如何验证是否成功,我也是参考了众多的文章,然后自己尝试了一下。小白安装不易

Can Caffe or Caffe2 be given input data directly from gpu?

假装没事ソ 提交于 2020-01-30 08:30:08
问题 I've read caffe2 tutorials and tried pre-trained models. I knew caffe2 will leverge GPU to run the model/net. But the input data seems always be given from CPU(ie. Host) memory. For example, in Loading Pre-Trained Models, after model is loaded, we can predict an image by result = p.run([img]) However, image "img" should be read in CPU scope. What I look for is a framework that can pipline the images (which is decoded from a video and still resides in GPU memory) directly to the prediction

Food101 SqueezeNet Caffe2 number of iterations

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

Android NDK make. Hundreds of “undefined reference error”s

◇◆丶佛笑我妖孽 提交于 2019-12-22 09:49:51
问题 When trying to build this sample project https://github.com/caffe2/AICamera/tree/master/app/src/main/cpp I get hundres of error: undefined reference s. Here are the first few lines of output: FAILURE: Build failed with an exception. * What went wrong: Execution failed for task ':app:externalNativeBuildDebug'. > Build command failed. Error while executing process /home/aidan/Android/Sdk/cmake/3.6.4111459/bin/cmake with arguments {--build /home/aidan/AndroidStudioProjects/AICamera/app/

Got confused after I extracted weights from Trained caffenet

无人久伴 提交于 2019-12-13 03:39:46
问题 So basically this are the dimensions of the weights from trained caffenet: conv1: (96,3,11,11) conv2: (256,48,5,5) conv3:(384,256,3,3) conv4: (384,192,3,3) conv5:(256, 192, 3 , 3) I am confused that although conv1 gives 96 channels as output why does conv2 only considers 48 while convolution? Am I missing something? 回答1: Yes, you missed the parameter 'group'. The convolution_param defined in the conv2 layer is given below.You can find out that parameter group is set to 2 as grouping the

Python/Caffe2: ImportError: No module named tools.setup_helpers.env

和自甴很熟 提交于 2019-12-08 08:37:35
问题 I cannot install the Python caffe2 module from the PyPi repository. When issuing sudo pip install caffe2 the following error occurs: $ sudo pip install caffe2 The directory '/home/user/.cache/pip/http' or its parent directory is not owned by the current user and the cache has been disabled. Please check the permissions and owner of that directory. If executing pip with sudo, you may want sudo's -H flag. The directory '/home/user/.cache/pip' or its parent directory is not owned by the current