Face Recognizer (laggy)

Analyzes video frame by frame and counts number of peoples then writes to csv

The csv file will be people.csv

Because the display of the video and analyzing of the frame is done in the same(main) thread, there will be lag when showing the video.

Algorithm Used

HOG (Histogram of Oriented Gradients)

Parameters (Explanation of parameters)

• winStride = (4, 4)
• padding = (8, 8)
• scale = 1.05

Getting Started

Run the script by specifying the video

python[3] detect.py -v "path to the video"

Prerequisites

The script is coded using python 3.6, opencv 3. And you will need opencv compiled with ffmpeg to read video

Installing

Install opencv3 on anaconda

conda install -c menpo opencv3

Or to compile opencv3 with ffmpeg follow instructions here https://github.com/menpo/conda-opencv3 or run these commands

$ conda install conda-build
$ git clone https://github.com/menpo/conda-opencv3
$ cd conda-opencv3
$ conda config --add channels menpo
$ conda build conda/
$ conda install /PATH/TO/OPENCV3/PACKAGE.tar.gz

Before compiling change the flag -DWITH_FFMPEG=0 to 1 on file conda/build.sh.

Then install other libraries using pip or pip3

pip[3] install imutils

Another reference on installing opencv on Ubuntu 16.04: http://www.pyimagesearch.com/2016/10/24/ubuntu-16-04-how-to-install-opencv/

Output

The output csv will be in this format

1.0,6
2.0,6
3.0,6
4.0,6
5.0,5
6.0,6
7.0,6
8.0,6
9.0,6

The Delimiter is ,. The first column is the frame number and the second column is the number of people in that frame.