Scanner: efficient video analysis at scale




  • Paper topic: Images
  • Software type: Code
  • Able to run a replicability test: True
  • Replicability score: 4
  • Software language: C/C++, Python
  • License: Apache License 2.0
  • Build mechanism: Makefile, CMakeLists, Not applicable (python, Matlab..)
  • Dependencies: tensorflow/caffe/opencv/eigen3/ffmpeg/boost/openpose/halide/storehouse/hwang/pybind/grpc/protobuf/libpqxx/cuda/cudnn
  • Documentation score {0,1,2}: 1
  • Reviewer: Julie Digne <>
  • Time spent for the test (build->first run, timeout at 100min): 50min

Source code information


I used the docker setting, it worked well (cpu). Was not able to install from source because of a problem with hwang (installed by although optional dependency). A jupyter notebook extremely detailed is provided and helps understand the code, so it would be very easy to adapt. I did not reproduce all the results in the paper (grayscale conversion worked well with docker).

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