Head_Pose_Estimation

-for more videos https://drive.google.com/drive/folders/1-OxlDhqQSYK1x3DutI27WlUmWQqnjnjz

• In this project we will draw the 3 position axis (pitch,yaw,roll) by predicting the 3 angels of each position by training 3 models to predict each angel.
• We will use AFLW2000 dataset with contains 2000
• We will use MediaPipe library and pycaret in both training and testing phases .
• PyCaret is an open-source, low-code machine learning library in Python that automates machine learning workflows.

Steps of the notebook:

-  Importing Libraries. 
-  Loading Data. 
-  Preparing the data for Training.
-  Prpcessing the Data.
-  Visualing Random image and drawing its points and axis to select best points
-  Using pycaret to get best models
-  Tune and Evaluate the best models (svr , huber) 
-  Blend them using pycaret 
-  Defining function for drawing the 3 axis.
-  Visualing Random image and drawing its points and axis.
-  Drawing the axis from the true labels on the image.
-  Testing the model on the image.
-  Testing the model on a video by processing its frames and drawing the axis on them.

🛠 tOOLS USED

Python, pycaret, OpenCV , svr , huber