Jacob Mccalip, Daemon Henry Mutka, Julio cantu
Our final machine vision project, VIZN, was made with the intention to collectively use what we learned in class to detect faces from different images. To do so we used Adaboost as the backbone and Cascade Classifiers as its framework to build the trained model. For detecting we also implemented a Skin Detection functionality to heavily reduce the data the model will need to sort through.
README.md
- This file.gitignore
- This file tells git which files to ignore.train.py
- Called to train and output a pkl of the trained datatest.py
- Used along with a 1 or 2 to call either test1 or test 2test1.py
- Basic training programs for the trained face detectortest2.py
- Advanced traning programs for the trained face detectorrequirements.txt
- Where the needed imports are locatedconfig.py
- Holds directory locationsface_detection_model.pkl
- Facial detection model based off of just AdaBoostingface_detection_cascade.pkl
- Facial detection model using AdaBoost and cascade clasifierssampleTestPyResults.txt
- Where the results are stored from the test programstesting.py
- Where testing of cropped faces, and non face images are cunducted using a cascade of boosted clasifiersskin_detection.py
- Used to create a(n) basic skin detection mask to use along with the trained modelprocessing.py
- where functionalities to load and process data is locatednms.py
-newSkin.py
- Used to create a(n) advanced skin mask using the UCI histogrammodel.py
- This file is holds the functions to save, load, or train the modelcascade.py
-boosting.py
- File used to cunduct the AdaBoosting techniqueUCI_Skin_NonSkin.txt
- Histogram for skin and non-skin data/important_outputs
- In the folder is where the basic and advanced data goes, along with the detected skin
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If you are running the code on your own machine, make sure python is installed and set up a virtual environment venv
. make sure to also have opencv
installed, you can do so you can use the requirements.txt
file by using the following command in your terminal:
pip install -r requirements.txt
In vs code you can use cmd + shift + p
to pull up the terminal to create a python enviornment, after chose python create
then venv
to finish setting up your enviornment run the command above in your terminal
You can run your code using the following commands:
The reposotory has a trained model, yet if you would like to train your own.
python train.py
To run the tests make sure your in the main directory, not src, and run the following command:
python test.py
After, you will a prompt that will ask if you are on Windows (1) or Linux (2) and will be asked to put in an input
Following you will recive another prompt asking if you would like to comence the Basic Testing (1) or the Advanced Testing (2)
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Basic Skin Mask | Advanced Skin Mask | Basic Test | Advanced Test |
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Original Photo
Basic Skin Mask | Advanced Skin Mask | Basic Test | Advanced Test |
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Original Photo
Basic Skin Mask | Advanced Skin Mask | Basic Test | Advanced Test |
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