yolo caffe

In the case of Caffe Runtest, the test mnist appears (copy others, as in memory) F0616 16:54:55.034394 3070141376 cudnn_conv_layer.cpp:53] Check Failed:status = = cudnn_status_success (4 vs. 0) Cudnn_status_internal_error Check failure stack trace: *** @ 0x112de33ad google::logmessage::sendtolog () @ 0x112de3ab3 google :: Logmessage::flush () @ 0x112de6d03 google::logmessagefatal::~logmessagefatal () @ 0x112de43b7 google:: Logmessagefatal::~log

After half a year, because of the needs of the paper, and re-start research Caffe. Thanks to the contribution of Niuzhiheng's GitHub great God, Caffe is already available under Windows. Reference to a lot of great God's blog, successfully configured in their own notebook Windows version of the Caffe. Now the configuration process and the configuration of the prob

Original address: https://www.zhihu.com/question/27982282 Gein Chen's answer many thanks —————————————————————————————————————————— 1. The first step of learning the program, first let the program run, see the results, so that there will be an intuitive feeling.Caffe's official Online Caffe | The Deep learning Framework provides a lot of examples, and you can easily start to train some existing classic models, such as lenet. I suggest starting with th

Voluminous a big article, there is no, these days have been tossing this thing, really no way, do not want to use Linux but, in order to Caffe, only so, install these things, encounter many problems, each problem will be tortured for a long time, probably the first time this is. Think, after the application, should still encounter a lot of problems it, but no way, Tiger!! One suggestion here is that if you want to make a big data set in the future, it

Configuration environment: WINDOWS-CAFFE-SSD + Windows7 X64 + VS2013 + matlab213a + Anconda2(CAFFE-SSD Microsoft's official Source code: Link: http://pan.baidu.com/s/1c12xAgw password: Vurt. NuGet will automatically configure the required libraries for CAFFE-SSD)Installed on the CPU, so there is no need to install Cuda and CUDNN. 1 do not download 3rdparty. 3rd p

, rigorous source of the implementation, combined with their own understanding, a concise, vivid way to simulate.Reading such code, is very easy, because the original very complex source code, after the author carefully choreographed and two times rewrite, it seems to be more amiable.Of course, we do not have to write books, but at least to learn to dismantle the source code, to simulate, simplify, two times rewrite the source code.Read a complex source code, remember above his business. The big

Caffe is reproduced on Cifar10 ResNet ResNet in the 2015 imagenet competition, the recognition rate reached a very high level, here I will use Caffe on Cifar10 to reproduce the paper 4.2 section of the CIFAR experiment. the basic module of ResNet Caffe Implementation the experimental results and explanations on CIFAR10 the basic module of ResNet In this paper, w

The previous time has been in the TensorFlow, now the internship company project needs to compare TensorFlow and Caffe in the image classification which better, so small I can now only put tensorflow aside, engage a caffe. There are a lot of such resources on the net, but we write all the same, run up there are many did not write understand, in order to use later, at the same time convenient for beginners l

Google, and Google is highly appreciative of snappy's many advantages, and snappy has been "designed to not crash even if it encounters corrupt or malicious input files," and is used by Google to compress petabytes of data in production environments. Its robustness and stability are evident. 4. OpenCV, this is not much to say. 5. Hdf5, just understand it as a file format. The full name is hierarchical data format, which can store different types of image and digital data in a file format, and c

The personal Practice code is as follows:#!/usr/bin/env sh# Create the imagenet lmdb inputs# n.b.SetThe path to the Imagenet train +Val Data dirsSet-Eexample=/home/wp/caffe/caffe-master/myself/00bDATA=/home/wp/caffe/caffe-master/myself/00bTOOLS=build/Toolstrain_data_root=/home/wp/c