Comments (4)
You should build it with C++ 11 support enabled. Add CXXFLAGS += -std=c++11 to your Makefile.config.
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Thanks, compiling problem solved. By the way, I tried your another code: https://github.com/eldar/deepcut. The demo_multiperson takes about 4 minutes to get the result for one image. How could I make the code in testing mode (not in demo mode) and make it slightly quicker?
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you should open the issues related to the multi-person pose estimation in the corresponding git repo. This is true, though, that current implementation runs on the order of several minutes on crowded images containing multiple overlapping people. Please refer to http://pose.mpi-inf.mpg.de/contents/insafutdinov16arxiv.pdf for run-time analysis. We will be working on exploring the ways of reducing run-time.
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Thanks for the explanation, the pose estimation results look impressive. I agree that I should report the issue in the other repo, sorry about that.
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Related Issues (19)
- make pycaffe issue HOT 1
- /BS/eldar/work/pose/exp/mpii-all-reg/data/all_stats.txt HOT 2
- Build in window
- How can I get array joint?
- Error in ubuntu while testing my own image HOT 4
- ResNet-50 HOT 5
- can i use your single person model to complete mulit person task?
- Problem in Demo HOT 1
- Out of memory while running demo HOT 11
- Can i know where to enable c++11 ? HOT 4
- Is it allowed to use for commercial purposes?
- make all pycaffe issue HOT 2
- does not compile under ubuntu 14.04 or 16.04 HOT 2
- confusing mix of Makefile.config.example and cmake HOT 1
- train code HOT 8
- Multi-person
- ID'ing detectors
- how to crop a single person img from the src image(MPII dataset) HOT 1
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