remi.bussiere
/
CV-Project-1-BUSSIERE-BEAUD
1
1
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

Mise à jour de 'README.md'

This commit is contained in:
Rémi BUSSIERE 2023-02-19 19:35:14 +01:00
parent d1a0963ec3
commit c79a4b8dc7
1 changed files with 3 additions and 3 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

6
README.md
View File

@ -2,7 +2,7 @@
This project has an objective of determine the heartrate of a person by analysing a 1 minute long video taken by a computer camera. 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 ##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. 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. Then, we use the ffmpeg package* to convert this video into a 15fps, 640x480 video.
@ -11,7 +11,7 @@ Then, we use the ffmpeg package* to convert this video into a 15fps, 640x480 vid
##SECOND STEP - Get the ROI position ##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. 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.
@ -24,7 +24,7 @@ The haarcascades is a pre-train model of machine learning developped for OpenCV
##THIRD STEP - Calculate the average color ##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. 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.