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mscnn crowd counting model

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Introduction

This is open source project for crowd counting. Implement with paper "Multi-scale Convolution Neural Networks for Crowd Counting" write by Zeng L, Xu X, Cai B, et al. For more details, please refer to arXiv paper

Contents

1. Installation
2. Preparation
3. Train/Eval
4. Details

Installation

1. Configuration requirements

python3.x

Please using GPU, suggestion more than GTX960

python-opencv
#tensorflow-gpu==1.0.0
#tensorflow==1.0.0
matplotlib==2.2.2
numpy==1.14.2

conda install -c https://conda.binstar.org/menpo opencv3
pip install -r requirements.txt

2. Get the code

git clone https://github.com/Ling-Bao/mscnn
cd mscnn

Preparation

1. ShanghaiTech Dataset. ShanghaiTech Dataset makes by Zhang Y, Zhou D, Chen S, et al. For more detail, please refer to paper "Single-Image Crowd Counting via Multi-Column Convolutional Neural Network" and click on here.

2. Get dataset and its corresponding map label Baidu Yun Password: sags

3. Unzip dataset to mscnn root directory

 tar -xzvf  Data_original.tar.gz

Train/Eval

Train is easy, just using following step.

1. Train. Using mscnn_train.py to evalute mscnn model

python mscnn_train.py

2. Eval. Using mscnn_eval.py to evalute mscnn model

python mscnn_eval.py

Details

1. Improving model structure. Add Batch Normal after each convolution layer.

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TAIL