GloriosaAI

Scripts:

• main.py: The selection menu for GloriosaAI

/scripts/

• trainer.py: Runs GloriosaAI trainer
• modelout.py: Output images from trained models with GloriosaAI
• video_encoder.py: Encode a video using GloriosaAI
• image-processor.py: Prepare images for GloriosaAI
• preprocessor_data.py: Dependency for GloriosaAI
• install_dependencies.py: Install dependencies

Prerequisite Folders:

Trainer

• training_data/class

Video Encoder

• output/video_frames (Also created by the Trainer)

ModelOut

• input/input_models (Copy the architecture and weights of both the discriminator and generator.)

Image-Processor

• unprocessed_images

trainer.py Hyperparameters:

• Epochs:

  • Controls the number of training iterations.

• Batch Size:

  • Determines the number of data samples processed in each training step.

• Latent Dimension:

  • Defines the size of the latent space in the generative model.

• Generation Interval:

  • Sets how often generated images are saved during training.

• Learning Rate:

  • Governs the step size during gradient descent optimization.

• Use Learning Rate Scheduler:

  • Specifies whether to use a learning rate scheduler during training.

• Random Seed:

  • Seeds the random number generator for reproducibility.

Prerequisites:

Package Version

---

absl-py 2.4.0 astunparse 1.6.3 certifi 2026.2.25 charset-normalizer 3.4.7 click 8.3.1 contourpy 1.3.3 cycler 0.12.1 Flask 2.1.1 flatbuffers 25.12.19 fonttools 4.62.1 gast 0.7.0 google-pasta 0.2.0 grpcio 1.80.0 h5py 3.14.0 idna 3.11 itsdangerous 2.2.0 Jinja2 3.1.6 keras 3.14.0 kiwisolver 1.5.0 libclang 18.1.1 markdown-it-py 4.0.0 MarkupSafe 3.0.3 matplotlib 3.8.2 mdurl 0.1.2 ml_dtypes 0.5.4 namex 0.1.0 numpy 1.26.2 opencv-python 4.8.1.78 opt_einsum 3.4.0 optree 0.19.0 packaging 26.0 Pillow 10.1.0 pip 26.0.1 protobuf 7.34.1 Pygments 2.20.0 pyparsing 3.3.2 python-dateutil 2.9.0.post0 requests 2.33.1 rich 14.3.3 setuptools 82.0.1 six 1.17.0 tensorflow 2.21.0 termcolor 3.3.0 typing_extensions 4.15.0 urllib3 2.6.3 Werkzeug 3.1.8 wheel 0.46.3 wrapt 2.1.2

Compiler:

• PyInstaller

Optional:

• A dataset of images for training (128 x 128 resolution, RGB format)

GloriosaAI - Art Showcase

How to Run:

python3 -m venv venv
source venv/bin/activate
pip install -r requirements.txt

pip install opencv-contrib-python

For GPU

nvidia-smi
pip install --upgrade pip
pip install --extra-index-url https://pypi.nvidia.com tensorrt-bindings==8.6.1 tensorrt-libs==8.6.1
pip install -U tensorflow[and-cuda]

For CPU

pip install tensorflow

Additional Packages

pip install numpy
pip install matplotlib
pip install Pillow
pip install opencv-python
pip install pyinstaller
pip install flask

python main.py

chmod +x setup.sh

• Gender-Age-ID Repository
• Detect-Face Repository
• Cursed GPT
• Image-Generator

Cursed Entertainment 2024