caffe

I used VGG 16-Layer Caffe model for image captions and I have several captions per image. Now, I want to generate a sentence from those captions (words). I read in a paper on LSTM that I should remove the SoftMax layer from the training network and provide the 4096 feature vector from fc7 layer directly to LSTM. I am new to LSTM and RNN stuff. Where should I begin? Is there any tutorial showing how to generate sentence by sequence labeling? AFAIK the master branch of BVLC/caffe does not yet support a recurrent layer architecture. You should pull branch recurrent from jeffdonahue/caffe . This

How can I change the solver parameter in Caffe through pycaffe? E.g. right after calling solver = caffe.get_solver(solver_prototxt_filename) I would like to change the solver's parameters (learning rate, stepsize, gamma, momentum, base_lr, power, etc.), without having to change solver_prototxt_filename . Maybe you can create a temporary file. First of all, load your solver parameters with from caffe.proto import caffe_pb2 from google.protobuf import text_format solver_config = caffe_pb2.SolverParameter() with open('/your/solver/path') as f: text_format.Merge(str(f.read()), solver_config) You

What is the use for average_loss ? Would someone please give an example of it or explain it in layman's terms? You can check in the caffe.proto file. Line 151 in the present version gives the following comment for average_loss: Display the loss averaged over the last average_loss iterations 来源： https://stackoverflow.com/questions/40190377/what-is-average-loss-field-in-caffe-solver-for

Is there a simple way (e.g. without modifying caffe code) to load wights from multiple pretrained networks into one network? The network contains some layers with same dimensions and names as both pretrained networks. I am trying to achieve this using NVidia DIGITS and Caffe. EDIT : I thought it wouldn't be possible to do it directly from DIGITS, as confirmed by answers. Can anyone suggest a simple way to modify the DIGITS code to be able to select multiple pretrained networks? I checked the code a bit, and thought the training script would be a good place to start, but I don't have in-depth

1、 ./include/caffe/common.hpp:5:27: fatal error: gflags/gflags.h: No such file or directory 解决办法：sudo apt-get install libgflags-dev 2、 ./include/caffe/util/mkl_alternate.hpp:14:19: fatal error: cblas.h: No such file or directory 解决办法：sudo apt-get install libblas-dev 3、 ./include/caffe/util/hdf5.hpp:6:18: fatal error: hdf5.h: No such file or directory 解决办法：在Makefile.config找到以下行并添加蓝色部分 INCLUDE_DIRS := $(PYTHON_INCLUDE) /usr/local/include /usr/include/hdf5/serial LIBRARY_DIRS := $(PYTHON_LIB) /usr/local/lib /usr/lib /usr/lib/x86_64-linux-gnu/hdf5/serial 4、 ./include/caffe/util/db_lmdb.hpp:8:18:

本文首发于个人博客 https://kezunlin.me/post/bcdfb73c/ ，欢迎阅读最新内容！ tensorrt fp32 fp16 tutorial with caffe pytorch minist model Series Part 1: install and configure tensorrt 4 on ubuntu 16.04 Part 2: tensorrt fp32 fp16 tutorial Part 3: tensorrt int8 tutorial Code Example include headers #include <assert.h> #include <sys/stat.h> #include <time.h> #include <iostream> #include <fstream> #include <sstream> #include <iomanip> #include <cmath> #include <algorithm> #include <cuda_runtime_api.h> #include "NvCaffeParser.h" #include "NvOnnxConfig.h" #include "NvOnnxParser.h" #include "NvInfer.h" #include "common.h"

The caffe is installed on the Ubuntu server,and it test is ok. I just run the following code on the Ubutun(16.04) cloud server: import caffe from caffe.proto import caffe_pb2 label_map = caffe_pb2.LabelMap() and I have run the command as following which provided by the internet, but there is still error: command: export PYTHONPATH=$/home2/challenge98/caffe/python:$PYTHONPATH error: Traceback (most recent call last): File "<stdin>", line 1, in <module> AttributeError: 'module' object has no attribute 'LabelMap' Could you guys give me some advices how to solve it. Thanks! tktktk0711 Should