MikeMpapa
commented
5 years ago Hi Keneth,
The mat files are needed only to repeat the experiments provided in the paper. They contain the true labels for the 11h dataset (D1) used for evaluation which unfortunately I cannot share due to copyrights. D2 and D3 though are free online and you can test the system there.
However if you wish to use the pretrained models for your own framework the only think you need to do is to load the model and evaluate it in your own dataset assuming that you know the ground truth labels. You will have to build your own code for that though using as a guideline the ClassifyWav.py
Thanks, Michalis Papakostas
PhD Candidate Heracleia - Human Centered Computing Lab Department of Computer Science University of Texas, Arlington
Στις Πέμ, 28 Φεβ 2019 στις 12:49 μ.μ., ο/η KennethEnevoldsen < notifications@github.com> έγραψε:
Dear Mike,
A group I am working with is intending to hopefully utilize this project in an upcoming publication. (assuming it generalise well to Danish) I have read previous issues and found xtluo-ai http:///xtluo-ai comments especially useful.
However I am currently running in to the problem stated in the title: "UnboundLocalError: local variable 'flagsIndGT' referenced before assignment"
Looking at "ClassifyWav.py", however I found the issue to be the missing '*_true.mat' file, which is seemingly a ground truth file. I however have no intention of using a ground truth, besides the initial performance testing.
Is it possible to utilize the already pretrained model, without such a file? Couldn't find any method in the readme nor in the code itself. I might however have missed something.
Thanks in advance, Kenneth Enevoldsen __ If relevant the script is currently run in using the caffe docker optimized for CPU: https://hub.docker.com/r/bvlc/caffe/
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KennethEnevoldsen
Dear Mike,
A group I am working with is intending to hopefully utilize this project in an upcoming publication. (assuming it generalise well to Danish) I have read previous issues and found xtluo-ai comments especially useful.
However I am currently running in to the problem stated in the title: "UnboundLocalError: local variable 'flagsIndGT' referenced before assignment"
Looking at "ClassifyWav.py", however I found the issue to be the missing '*_true.mat' file, which is seemingly a ground truth file. I however have no intention of using a ground truth, besides the initial performance testing.
Is it possible to utilize the already pretrained model, without such a file? Couldn't find any method in the readme nor in the code itself. I might however have missed something.
Thanks in advance, Kenneth Enevoldsen __ If relevant the script is currently run in using the caffe docker optimized for CPU: https://hub.docker.com/r/bvlc/caffe/