# PyramidScaleNetwork

**Repository Path**: wang_wei_973667927/PyramidScaleNetwork

## Basic Information

- **Project Name**: PyramidScaleNetwork
- **Description**: PSNet，多尺度人群计数网络
- **Primary Language**: Python
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2021-12-15
- **Last Updated**: 2021-12-15

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# Pyramid_Scale_Network
This is the PyTorch version repo for "Exploit the potential of Multi-column architecture for Crowd Counting", which delivered a state-of-the-art, straightforward and end-to-end architecture for crowd counting tasks. We also recommend another work on crowd counting([Deep Density-aware Count Regressor](https://github.com/GeorgeChenZJ/deepcount)), which is accepted by ECAI2020.

# Datasets
ShanghaiTech Dataset

# Prerequisites
We strongly recommend Anaconda as the environment.  
  
Python: 3.6  
  
PyTorch: 1.5.0

# Train & Test
1、python make_dataset.py # generate the ground truth. the ShanghaiTech dataset should be placed in the "datasets" directory.  
2、python train.py # train model  
3、python val.py # test model

# Results
partA: MAE 55.5 MSE 90.1  
  
partB: MAE 6.8 MSE 10.7