# CV-Project-1-BUSSIERE-BEAUD

This project has an objective of determine the heartrate of a person by analysing a 1 minute long video taken by a computer camera. 

##FIRST STEP - Get the video##

To get the video, we need a normal camera ( like a laptop camera ) and record a ~1min long video of ourselves, in this case : Rémi.
Then, we use the ffmpeg package* to convert this video into a 15fps, 640x480 video.

*sudo apt install ffmpeg on debian distribution



##SECOND STEP - Get the ROI position##

The ROI ( Region of interest ) is important here because we only need the average color of the person's head, the surrounding is considerate here as noise. 

To get the ROI, we use a simple solution delivered by OpenCV* in python called haarcascades.

*pip install opencv-python

The haarcascades function will return 4 coordinates that will surround the person's head.
The haarcascades is a pre-train model of machine learning developped for OpenCV where you can find here : https://github.com/opencv/opencv/tree/master/data/haarcascades



##THIRD STEP - Calculate the average color##

Then, we have the coordinates, and we compute the average between each red composents of each pixel inside the square, and we repeat it for blue and green. Then, we have as an output one color/frame.

You can find a picture of the haarcascades algotithm in the picture section.

We then export a .txt file with all the average color to use it in an octave code.



### LA TU METS TON CODE NATHAN ###

POSSIBLE ALTENATIVES

In order to find the best possible ROI, we need some other algorithm than haarcascades. So that's why we used the mediapipe* library, wich is a way better algorithm, it's also a pre-trained model but much more complete. We can see here a picture of the results using the mediapipe library, where the ROI is more precise.

*pip install mediapipe
more informations here : https://github.com/google/mediapipe