Before delving into gpen-bfr-2048.pth , it's essential to understand what .pth files are. In PyTorch, models are typically saved in the .pth or .pt format. These files contain the model's parameters or weights, which are crucial for the model to make predictions. When a model is trained, its weights are adjusted to minimize a loss function, and saving these weights allows for the model to be loaded later for inference (making predictions) without needing to retrain it.
: It uses a Generative Adversarial Network (GAN) to "fill in" realistic facial details that are missing from the original photo. gpen-bfr-2048.pth
# Load the model model = torch.load('gpen-bfr-2048.pth', map_location=torch.device('cpu')) Before delving into gpen-bfr-2048
GPEN addresses the challenge of restoring faces from "blind" degradations (unknown combinations of blur, noise, and compression) by embedding a pretrained Generative Adversarial Network (GAN) into a U-shaped Deep Neural Network (DNN). When a model is trained, its weights are