Hypraptive BearID project. FaceNet for bears.
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tools
.gitignore
CMakeLists.txt
LICENSE.txt
README.md
bearchip.cpp
bearembed.cpp
bearface.cpp
bearfacechip.cpp
bearid.cpp
bearsvm.cpp

README.md

bearid

Hypraptive BearID project code repository. For more information, read the hypraptive blog.

Pre-Requisites

  • dlib - download and install somwhere. You should have OpenCV and CUDA and other packages which are helpful for dlib.
  • boost

Build

Uses cmake flow:

cd bearid
mkdir build
cd build
cmake -DDLIB_PATH=<path_to_dlib> ..
cmake --build . --config Release

Running

  • Bearchip - finds bear faces, aligns and crops
    • ./bearchip <mmod_dog_hipsterizer.dat> <image_file or image_path>
  • Bearembed - uses a set of bear faces to train a 128D embedding
    • ./bearembed -train <face_chip_dir>
    • ./bearembed -test <face_chip_dir>
    • ./bearembed -embed <embedded_dir> <face_chip_dir>
  • Bearsvm - uses a set of embeddings to train and SVM one-vs-one classifier
    • ./bearsvm <embedded_dir>
  • Bearid - puts it all together
    • ./bearid <image_file>

Tools

There are some python tools and scripts in the tools directory for managing datasets and evaluating results.

Data Sources

Brooks Falls, Katmai National Park, Alaska, USA

Glendale Cove, Knights Inlet, British Columbia, Canada