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LCFCN - ECCV 2018

Where are the Blobs: Counting by Localization with Point Supervision

[Paper][Video]

Requirements

  • Pytorch version 0.4 or higher.

Description

Given a test image, the trained model outputs blobs in the image, then counts the number of predicted blobs (see Figure below).

Shanghai test image

Running the saved models

  1. Download the checkpoints,
bash checkpoints/download.sh
  1. Output the saved results,
python main.py -m summary -e trancos
  1. Re-evaluate the saved model,
python main.py -m test -e trancos

Training the models from scratch

To train the model,

python main.py -m train -e trancos

Benchmark

Method Trancos Pascal
ResFCN 3.39 0.31
Paper 3.32 0.31

Citation

If you find the code useful for your research, please cite:

@Article{laradji2018blobs,
    title={Where are the Blobs: Counting by Localization with Point Supervision},
    author={Laradji, Issam H and Rostamzadeh, Negar and Pinheiro, Pedro O and Vazquez, David and Schmidt, Mark},
    journal = {ECCV},
    year = {2018}
}