Gpen-bfr-2048.pth — |work|

gpen-bfr-2048.pth is a high-resolution PyTorch model file used for Blind Face Restoration (BFR). It is part of the GAN Prior Embedded Network (GPEN) framework, which specializes in restoring severely degraded, blurry, or low-quality facial images into clear, high-fidelity results. Technical Overview

resolutions, the 2048 variant is uniquely optimized for high-detail outputs, often referred to as the "selfie" model. Key Technical Specifications Target Resolution: Trained on gpen-bfr-2048.pth

# Use the model for inference input_data = torch.randn(1, 3, 224, 224) # Example input output = model(input_data)

. It is specifically designed to restore or enhance low-quality facial images—such as those that are blurry, noisy, or low-resolution—into clear, high-fidelity portraits. Key Specifications & Context Model Type gpen-bfr-2048

Performance characteristics

• Strong hallucination of plausible high-frequency details; may alter fine identity cues if over-applied.
• Best results when faces are frontal or near-frontal; extreme poses/occlusions reduce fidelity.
• Computationally intensive: needs GPU with substantial VRAM for 2048 outputs (recommend >=16–24 GB for batch processing).
• Inference speed depends on hardware; single-image 2048 restoration can take seconds to tens of seconds on consumer GPUs.