priyanka-kasture/crowd-counting-with-mcnns

Crowd counting on the ShanghaiTech dataset, using multi-column convolutional neural networks.

Crowd Counting with MCNNs - MindSpark Hackathon 2018

Crowd counting on the ShanghaiTech dataset, using multi-column convolutional neural networks.

This is an unofficial implementation of CVPR 2016 paper "Single Image Crowd Counting via Multi Column Convolutional Neural Network".

Note: Predictions can be made. The work on heatmap generation in under progress.

Installation

• Install Tensorflow and Keras
  
• Install OpenCV
  
• Clone this repository (in case you don't want train the model and want to use the pre-trained one).
  

Data Setup

Download ShanghaiTech Dataset from:

• Dropbox: https://www.dropbox.com/s/fipgjqxl7uj8hd5/ShanghaiTech.zip?dl=0
  
• Baidu Disk: http://pan.baidu.com/s/1nuAYslz
  

Create a folder: ROOT/data/original/shanghaitech/

Here ROOT is the folder conatining all files, it's the main folder. (Don't create a folder called ROOT!)

• Save "part_A" under ROOT/data/original/shanghaitech/
  
• Save "part_B" under ROOT/data/original/shanghaitech/
  
• Got to ROOT/data_preparation/
  
• There, run create_gt_test_set_shtech.m in matlab/octave to create ground truth files for test data.
  
• Then go to ROOT/data_preparation/ again.
  
• run create_training_set_shtech.m in matlab to create training and validataion set along with ground truth files.
  

- Save the ground truth csv files in ROOT/data/
That completes data-setup!

Test

• Follow steps 1, 2, 3, 4 and 5 from Data-Setup.
  
• Download pre-trained model files:
  [Shanghai Tech A] : https://www.dropbox.com/s/8bxwvr4cj4bh5d8/mcnn_shtechA_660.h5?dl=0
  [Shanghai Tech B] : https://www.dropbox.com/s/kqqkl0exfshsw8v/mcnn_shtechB_110.h5?dl=0
  

- Save the model files under: ROOT/final_models
- Finally run: test.py

Train

• Not recommended unless you have a great processor, or a GPU, because training takes a lot of time. Load the pre-trained model and test it on the test set instead.
  

• For tensorflow:
  run from prompt: python3 train.py A(or B)
  Model is saved to modelA/ or modelB/.
  

• For keras: run: python3 keras_train.py B
  model is saved to keras_modelB/
  

crowd-counting-with-mcnns's Issues

type error!

Hello, I have this problem:
Image Loading!
Traceback (most recent call last):
File "test.py", line 26, in
mcnn.predict()
File "C:\Users\Administrator\Crowd-Counting-with-MCNNs\network.py", line 286, in predict
img = (img - 127.5) / 128
TypeError: unsupported operand type(s) for -: 'NoneType' and 'float'

an array type can't be broadcast? I don't know what it is mean.

Give a single picture by a phone

How can I get single picture by photoing picture?
For example, I want to know my phone's picture whether coule be known

The keras model size~

Hello, I am testing different models to compare their performance.
I am confused about keras model size :'weights.h5' 562kB.
Thanks a lot.

how to run create_gt_test_set_shtech.m in matlab/octave

conv_m = (conv_m)

What does‘ conv_m = conv_m’ mean? i dont understand