https://github.com/cleder/login-picture
📸️ Take a picture when you login 🥳️
https://github.com/cleder/login-picture
face-detection face-recognition hacktoberfest opencv opencv-python
Last synced: about 1 year ago
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📸️ Take a picture when you login 🥳️
- Host: GitHub
- URL: https://github.com/cleder/login-picture
- Owner: cleder
- Created: 2020-11-07T16:26:09.000Z (over 5 years ago)
- Default Branch: main
- Last Pushed: 2025-04-01T08:10:34.000Z (about 1 year ago)
- Last Synced: 2025-04-01T09:24:36.636Z (about 1 year ago)
- Topics: face-detection, face-recognition, hacktoberfest, opencv, opencv-python
- Language: Python
- Homepage:
- Size: 17 MB
- Stars: 5
- Watchers: 2
- Forks: 0
- Open Issues: 4
-
Metadata Files:
- Readme: README.md
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README
python script that takes a picture from you webcam when it detects or recognizes a face.
# Installation
## Linux
Execute the installation script with `./install.sh`.
This will create a virtual environment and install the requirements.
It will also create an executable bash script `capture-login.sh` in your home directory.
You can run this as a [startup script](https://www.howtogeek.com/686952/how-to-manage-startup-programs-on-ubuntu-linux/) to take your photo whenever you login.
## Windows
Install Python (3.10) from the Windows store.
Open Power Shell and run `pip install opencv-python`
Create a shortcut on your Desktop, enter `python.exe C:\path\to\directory\detcap.py` as the command to run.
You can run this shortcut [on startup](https://superuser.com/questions/954950/run-a-script-on-start-up-on-windows-10) to take a photo when you login.
# Face detection
The script `capture-login.sh` will terminate and write a picture of you into the directory `~/Pictures/login-capture` once it detected
a face looking into the webcam.
# Run from commandline
Activate the virtualenv with `source venv/bin/activate`.
Run the script with `python detcap.py`.
This will open a fullscreen window and take a picture when a face is detected. The picture will be stored in `~/Pictures/login-capture/` with the username and current date and time as the name.
# Face recognition
## Required libraries for ubuntu
`sudo apt-get install build-essential cmake libopenblas-dev liblapack-dev libx11-dev libgtk-3-dev`
## Training
Once you have captured a decent amount of pictures you can compute face embedding vectors for your images with `python encode_images.py`.
This will write an encoding file next to the original captured image of yor face with the extension `.cnn-encoded.pickle`.
No embeddings will be written for pictures where more than one face was detected.
## Recognize your face on login
Test the recognizer with `python recognize_me.py` and see how it performs.
It will save the recognized image along with the embedding once your face was recognized.
You may want to fine tune the `tolerance` parameter in `recognize_me.py`.
Run `recognize-login.sh` on startup, the window will close once your face has been recognized.
The picture will be stored with its encoding in `~/Pictures/login-capture/` and will be used for future recognitions.
# Background
I used [howdy](https://github.com/boltgolt/howdy) to have a facial recognition login.
With this tool you can capture a picture on every login which can be used to train the howdy models.
It may also be fun to [create a video how you look over time](https://www.youtube.com/watch?v=wAIZ36GI4p8)
## Create time lapse of your pictures
I used [Face-Alignment](https://github.com/SajjadAemmi/Face-Alignment) as a preprocessor.
### Animated GIF with imagemagic
The images were resized and converted to gray-scale with the `convert` command of imagemagick:
```
find /path/to/input/ -iname '*.jpg' -exec convert \{} -verbose -colorspace Gray -set filename:base "%[basename]" -resize 256\> "/path/to/output/%[filename:base].jpg" \;
```
Afterwards you can create an animated GIF in the `/path/to/output/` directory with:
```
convert -delay 15 -loop 0 *.jpg timelapse.gif
```
### Video with ffmpeg
Alternatively you can create a video with ffmpeg:
```
ffmpeg -framerate 5 -pattern_type glob -i '*.jpg' -c:v libx264 -r 30 -vf format=gray,scale=256:256 output.mp4
```
ffmpeg -framerate 5 -pattern_type glob -i 'me/*.jpg' -c:v libx264 -r 30 -vf format=gray,scale=256:256,normalize=blackpt=black:whitept=white:smoothing=20:independence=0.5 output.mp4