This repository offers a comprehensive collection of preprocessing functions and deep learning techniques. It supports various features including audio processing, video analysis, text feature extraction, utility functions, and visualization tools, making it a versatile toolkit for multimodal data processing and analysis.
| Audio | Video | Text | Utils |
|---|---|---|---|
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pip install exordium[all]
pip install exordium
The following extras will install the base and specific dependencies for using TDDFA_V2.
pip install exordium[tddfa]
You can install multiple optional dependencies as well.
pip install exordium[tddfa,audio]
| Extras Tag | Description |
|---|---|
| audio | dependencies to process audio data |
| text | dependency to process textual data |
| tddfa | dependencies of TDDFA_V2 for landmark and headpose estimation, or related transformations |
| detection | dependencies for automatic face detection and tracking in videos |
| video | dependencies for various video feature extraction methods |
| all | all previously described extras will be installed |
Note: If you are not sure which tag should be used, just go with the all-mighty "all".
git clone https://github.com/fodorad/exordium
cd exordium
pip install -e .[all]
pip install -U -r requirements.txt
python -m unittest discover -s test
LinMulT is trained for categorical and dimensional emotion estimation, emotion intensity, and sentiment estimation tasks. The network is trained on 4 tasks, using 10 public benchmark databases.
LinMulT is trained for blink presence detection and eye state recognition tasks. Our results demonstrate comparable or superior performance compared to state-of-the-art models on 2 tasks, using 7 public benchmark databases.
LinMulT is trained for Big Five personality trait estimation using the First Impressions V2 dataset and sentiment estimation using the MOSI and MOSEI datasets.