caffe

问题 I am using caffe net with python. I have train.txt file like this: train/1175-c/b0a1.bmp b0a1 train/1175-c/b0a2.bmp b0a2 train/1175-c/b0a3.bmp b0a3 train/1175-c/b0a4.bmp b0a4 train/1175-c/b0a5.bmp b0a5 train/1175-c/b0a6.bmp b0a6 train/1175-c/b0a7.bmp b0a7 train/1175-c/b0a8.bmp b0a8 train/1175-c/b0a9.bmp b0a9 train/1175-c/b0aa.bmp b0aa my questions: Can I use hex instead of int at the end of each line? About the label, does it need to start from 0 Or Should I change the above to: train/1175-c

问题 I'm working with caffe framework and I would like to train the next network: When I execute the next command: caffe train --solver solver.prototxt The error it throws: `F0802 14:31:54.506695 28038 insert_splits.cpp:29] Unknown bottom blob 'image' (layer 'conv1', bottom index 0) *** Check failure stack trace: *** @ 0x7ff2941c3f9d google::LogMessage::Fail() @ 0x7ff2941c5e03 google::LogMessage::SendToLog() @ 0x7ff2941c3b2b google::LogMessage::Flush() @ 0x7ff2941c67ee google::LogMessageFatal::

问题 if you are using a custom python layer - and assuming you wrote the class correctly in python - let's say the name of the class is "my_ugly_custom_layer" ; and you execute caffe in the linux command line interface, how do you make sure that caffe knows how to find the file where you wrote the class for your layer? do you just place the .py file in the same directory as the train.prototxt? or if you wrote a custom class in python you need to use the python wrapper interface? 回答1: Your python

问题 I'm trying to use the MINST Caffe example via the C++ API, but I'm having a bit of trouble working out how to restructure the network prototxt file I'll deploy after training. I've trained and tested the model with the original file (lenet_train_test.prototxt), but when I want to deploy it and make predictions like in the C++ and OpenCV example, I realise I have to modify the input section to make it similar to the deploy.prototxt file they have. Can I replace the information in the training

问题 I want to use caffe deep learning. when I want to run caffe-windows\build_win I recive an error.what is problem? how can I resolve it? caffe is best for deep learning and I want to use it. I installed anaconda, visual studio 2015, cmake, cuda and I want to use caffe now. C:\Users\mohsen\Desktop\Propozal\DeepLearning\Install option for caffe\caffe-win dows>scripts\build_win The system cannot find the drive specified. The system cannot find the drive specified. INFO: ===========================

问题 I installed Caffe on Linux successfully. Then I failed to make it work with Matlab. So I installed it with Python following the tutorial of Pete Warden. However, I never used Python before I just run the command "python python/classify.py --print_results examples/images/cat.jpg foo" and it works. My question is how can I test calssify.py for a set images rather than a single image? I tried to read images from test directory as following cd caffe Python Import os For file in os.listdir(

问题 If I define multiple loss layers in a network, will there be multiple back propagation happening from those ends to the beginning of the network? I mean, do they even work that way? Suppose I have something like this: Layer1{ } Layer2{ } ... Layer_n{ } Layer_cls1{ bottom:layer_n top:cls1 } Layer_cls_loss1{ type:some_loss bottom:cls1 top:loss1 } Layer_n1{ bottom:layer_n .. } Layer_n2{ } ... layer_n3{ } Layer_cls2{ bottom:layer_n3 top:cls2 } Layer_cls_loss2{ type:some_loss bottom:cls2 top:loss2

问题 I'm trying to reshape the size of a convolution layer of a caffemodel (This is a follow-up question to this question). Although there is a tutorial on how to do net surgery, it only shows how to copy weight parameters from one caffemodel to another of the same size. Instead I need to add a new channel (all 0) to my convolution filter such that it changes its size from currently ( 64 x 3 x 3 x 3 ) to ( 64 x 4 x 3 x 3 ). Say the convolution layer is called 'conv1' . This is what I tried so far:

问题 I want to change the loss calculation method in loss layer when the iteration times reach a certain number. In order to realize it I think I need to get the current learning rate or iteration times, then I use if phrase to choose changing loss calculation method or not. 回答1: You can add a member variable in Caffe class to save the current learning rate or iteration times and access it in the layer where you want. For example, to get the current iteration times where you want you need to make

问题 I am trying to compile caffe with python interface on an Ubuntu 14.04 machine. I have installed Anaconda and opencv with conda install opencv . I have also installed all the requirement stipulated in the coffee and changed the commentary blocks in makefile.config so that PYTHON_LIB and PYTHON_INCLUDE point towards Anaconda distributions. When I am calling make all , the following command is issued: g++ .build_release/tools/caffe.o -o .build_release/tools/caffe.bin -pthread -fPIC -DNDEBUG -O2