piergiaj / caffe-deconvnet Goto Github PK

Its not compiling with rc4

In file included from ./include/caffe/vision_layers.hpp:10:0,
from src/caffe/layers/pooling_switches_layer.cpp:9:
./include/caffe/common_layers.hpp:10:33:

caffe/data_layers.hpp: No such file or directory.

Am getting this error while compiling .. Do you know why?

ylee3@sviyer:~/caffe$ make pycaffe
CXX/LD -o python/caffe/_caffe.so python/caffe/_caffe.cpp
In file included from ./include/caffe/layer.hpp:10:0,
from ./include/caffe/caffe.hpp:10,
from python/caffe/_caffe.cpp:17:
./include/caffe/layer_factory.hpp: In function ‘void caffe::init_module__caffe()’:
./include/caffe/layer_factory.hpp:87:17: error: ‘static std::string caffe::LayerRegistry::LayerTypeList() [with Dtype = float; std::string = std::basic_string]’ is private
static string LayerTypeList() {
^
python/caffe/_caffe.cpp:218:53: error: within this context
bp::def("layer_type_list", &LayerRegistry::LayerTypeList);
^
Makefile:445: recipe for target 'python/caffe/_caffe.so' failed
make: *** [python/caffe/_caffe.so] Error 1

hi, when I download the code and just cd to the python-demo dir , run the 'python test_deconv.py ' command,, then it throw an error like blew:

I0527 20:22:11.013113 17197 layer_factory.hpp:77] Creating layer input
I0527 20:22:11.013123 17197 net.cpp:84] Creating Layer input
I0527 20:22:11.013126 17197 net.cpp:380] input -> data
I0527 20:22:11.013139 17197 net.cpp:122] Setting up input
I0527 20:22:11.013146 17197 net.cpp:129] Top shape: 10 3 227 227 (1545870)
I0527 20:22:11.013147 17197 net.cpp:137] Memory required for data: 6183480
I0527 20:22:11.013150 17197 layer_factory.hpp:77] Creating layer conv1
I0527 20:22:11.013155 17197 net.cpp:84] Creating Layer conv1
I0527 20:22:11.013159 17197 net.cpp:406] conv1 <- data
I0527 20:22:11.013161 17197 net.cpp:380] conv1 -> conv1
I0527 20:22:11.182510 17197 net.cpp:122] Setting up conv1
I0527 20:22:11.182545 17197 net.cpp:129] Top shape: 10 96 55 55 (2904000)
I0527 20:22:11.182548 17197 net.cpp:137] Memory required for data: 17799480
I0527 20:22:11.182562 17197 layer_factory.hpp:77] Creating layer relu1
I0527 20:22:11.182570 17197 net.cpp:84] Creating Layer relu1
I0527 20:22:11.182572 17197 net.cpp:406] relu1 <- conv1
I0527 20:22:11.182575 17197 net.cpp:367] relu1 -> conv1 (in-place)
I0527 20:22:11.182678 17197 net.cpp:122] Setting up relu1
I0527 20:22:11.182696 17197 net.cpp:129] Top shape: 10 96 55 55 (2904000)
I0527 20:22:11.182698 17197 net.cpp:137] Memory required for data: 29415480
I0527 20:22:11.182699 17197 layer_factory.hpp:77] Creating layer pool1
F0527 20:22:11.182725 17197 layer_factory.hpp:81] Check failed: registry.count(type) == 1 (0 vs. 1) Unknown layer type: PoolingSwitches (known types: AbsVal, Accuracy, ArgMax, BNLL, BatchNorm, BatchReindex, Bias, Concat, ContrastiveLoss, Convolution, Crop, Data, Deconvolution, Dropout, DummyData, ELU, Eltwise, Embed, EuclideanLoss, Exp, Filter, Flatten, HDF5Data, HDF5Output, HingeLoss, Im2col, ImageData, InfogainLoss, InnerProduct, Input, LRN, LSTM, LSTMUnit, Log, MVN, MemoryData, MultinomialLogisticLoss, PReLU, Parameter, Pooling, Power, Python, RNN, ReLU, Reduction, Reshape, SPP, Scale, Sigmoid, SigmoidCrossEntropyLoss, Silence, Slice, Softmax, SoftmaxWithLoss, Split, TanH, Threshold, Tile, WindowData)
*** Check failure stack trace: ***
Aborted (core dumped)

because I am not familiar with caffe, so pls help me how to solve the problem , thanks

Could you include the "../test/butterfly.jpg" into the repo? That would make it easier to actually run the demo and play around with it. Thanks!

Thanks for the nice visualization tool~
However, when I plug in a single strongest activation in a specific feature map as the input, the output sometimes become nan in the pixel space. Could you remind me the reason? Thanks.

I ran the demo code available in python-demo/ folder for the butterfly test image. The output is very different from what is expected based on the publication (ECCV 2014 - https://www.cs.nyu.edu/~fergus/papers/zeilerECCV2014.pdf). It is attached below:-

I am using the caffe fork at https://github.com/piergiaj/caffe

make runtest fails at one of the test cases
[ RUN ] NetUpgradeTest.TestUpgradeV1LayerType
/media/data/aravindh/Software/caffe/piergiaj/caffe/src/caffe/test/test_upgrade_proto.cpp:2897: Failure
Value of: V1LayerParameter_LayerType_IsValid(i)
Actual: false
Expected: true
[ FAILED ] NetUpgradeTest.TestUpgradeV1LayerType (1 ms)
[----------] 4 tests from NetUpgradeTest (13 ms total)

Thanks for releasing your excellent work. I have run the demo in the deconvnet-python-demo file folder ,and I got the outputs. The following pictures are originated from “pool5” as shown in your python code.

Besides, I want know how to get the deconvolutional outputs from other layers’ feature map. I have tried to change some code in line 68 of the test_deconv.py(change pool5 to pool4). However, I met some errors here.

In addition, Could you tell me how to use other models to perform deconvolution and draw the outputs?
Thank you very much.

Hi~ Thank you for developing such a nice visualization tool. Just a small question regrading the test_deconv.py you provided as the demo. If I recall correctly it was said in Matthew's paper (http://www.matthewzeiler.com/pubs/arxive2013/eccv2014.pdf) that this deconvnet could only be used to visualize a single activation in a certain feature map, and thus we have to set the other activations to zero. While the following lines in test_deconv.py

feat = net.blobs['pool5'].data
feat[0][feat[0] < 150] = 0

seems to set only the activations smaller than 150 to zero, and I wonder if this might contradict with the original idea of the paper?
Thank you!

First of all, I would seriously like to appreciate you for your great work on deconvolution. I followed your steps regarding adding the extra modified layers like, inv-pooling, pooling_switches_layer, etc. and re-building the caffe. After giving the command "make all", I encountered an issue regarding recognizing 'PoolingSwitchesLayer" like : Check failed: registry.count(type) == 1 (0 vs. 1) Unknown layer type: PoolingSwitches
Any how I tried creating pooling_switches_layer.hpp file and added this to caffe/include/layers path and started re-building it. Later on, it gave me the message like, : poolingSwiches is already registered. As a result of which I overcame to this issue. and after giving othr commands like : make test, make runtest. I tried executing the "test_deconv.py" in the terminal from the path: "caffe/caffe-deconv-master/python-demo " , which now gave me the error which i encountered initially i.e. "Check failed: registry.count(type) == 1 (0 vs. 1) Unknown layer type: PoolingSwitches" during the time of creation of "pool1".
May be I am using the wrong .hpp file for this "pooling_switches_layer.cpp", or may be else which I could not find out. Please help me out with this issue and if possible can you plz send me the hpp file for this poolingswitches layer. I will be highly grateful to you. Kindly reply.

wow, great work, visualize model is very important for tunning model.
does this also work for vgg and googlenet?

/include/caffe/vision_layers.hpp:361:14: error: ‘PowerLayer’ was not declared in this scope
shared_ptr<PowerLayer > square_layer_;

so many errors there.

Thanks for releasing your excellent code.I split inv_pooling_layer、pooling_switches_layer、slice_half_layer,and put them in new caffe /include/caffe/layers and /src/caffe/layers respectively,and re-registration the new layers in caffe,I have already compiled the caffe. Then I use you demo test_deconv.py but I can not get same reuselts in the paper (ECCV 2014 - https://www.cs.nyu.edu/~fergus/papers/zeilerECCV2014.pdf).Can you give me some advises to solve it.And Can you tell me the caffe version that you used.I'm looking forward to the correct solution.Thank you very very much.

When I read the paper,and I met a question. How can I receive the figure 2 of this paper??
what the top 9 activations stand for ? if it stand for the last layer's activation,why layer 2-5 is different things???