An experiment with crowd counting. Trains a keras model in python for use with Rails and iOS CoreML.
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  1. Rails application that interacts with a crowd counting python machine learning service via gRPC.
  2. iOS app and macOS Playground that uses a CoreML pipeline to count the number of people in an image.

For an overview of the machine learning and Rails application, please visit this blog post.

Click on the individual folders for README's specific to each section.

Checkout with git-lfs

We use git-lfs to store images in git. For a faster check out, please first do:

git lfs fetch
git pull

/secrets folder and Google Cloud

$ cat .envrc
export CLOUDSDK_PYTHON=/Users/dimroc/.pyenv/versions/miniconda2-4.1.11/bin/python2
export GOOGLE_APPLICATION_CREDENTIALS=../secrets/gcloudstorage.development.json
gcloud config set project counting-company-production



  • Multi-scale Convolutional Neural Networks for Crowd Counting
    Lingke Zeng, Xiangmin Xu, Bolun Cai, Suo Qiu, Tong Zhang
    Page PDF
  • Fully Convolutional Crowd Counting On Highly Congested Scenes
    Mark Marsden, Kevin McGuinness, Suzanne Little and Noel E. O’Connor
  • Multi-Source Multi-Scale Counting in Extremely Dense Crowd Images
    Haroon Idrees, Imran Saleemi, Cody Seibert, Mubarak Shah
    IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), 2013
  • From Semi-Supervised to Transfer Counting of Crowds
    C. C. Loy, S. Gong, and T. Xiang
    in Proceedings of IEEE International Conference on Computer Vision, pp. 2256-2263, 2013 (ICCV)
    PDF Project Page
  • Cumulative Attribute Space for Age and Crowd Density Estimation
    K. Chen, S. Gong, T. Xiang, and C. C. Loy
    in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, pp. 2467-2474, 2013 (CVPR, Oral)
    PDF Project Page
  • Crowd Counting and Profiling: Methodology and Evaluation
    C. C. Loy, K. Chen, S. Gong, T. Xiang
    in S. Ali, K. Nishino, D. Manocha, and M. Shah (Eds.), Modeling, Simulation and Visual Analysis of Crowds, Springer, vol. 11, pp. 347-382, 2013
  • Feature Mining for Localised Crowd Counting
    K. Chen, C. C. Loy, S. Gong, and T. Xiang
    British Machine Vision Conference, 2012 (BMVC)
    PDF Project Page