HumanPose-ArtHistory

Human pose analysis in art-history: 2D pose analysis, clustering and visualization

Project structure

The project contains three scripts:

• preprocessing.py: takes the .json file of a dataset exported from Supervisely and outputs a .txt file where each row contains the (x,y) coordinates for the 24 keypoints of each image, and a corresponding file with the angles of each pair of keypoints rotated according to the torso.
• clustering.py: clusters the datasets using k-means and creates 2D and 3D plots using PCA.
• tsne.py: clusters the datasets using k-means and creates 2D and 3D plots using tsne. Two cases are tested: The first one takes into account inly the keypoints of the human posture, whereas the second one uses both the keypoints ans the torso rotation angles.
• torso_clustering.py: clusters the datasets using only the torso rotation angles.
• Visualization.py: helper functions for visualization.
• image_resize.py: resizes an imput image.

Installation

To run the project you have to execute the following steps:

1. Create the virtual environment humanpose:

python -m venv humanpose

2. Activate the virtual environment:

For windows

humanpose\Scripts\activate.bat

For Linux

source humanpose/bin/activate

3. Install the dependencies:

pip install -r requirements.txt

4. Run the scripts

python preprocessing.py
python clustering.py
python tsne.py
python torso_clustering.py