def get_encoder(): backbone = models.resnet50(pretrained=False) # Remove classification head and the final BN (keep conv layers) modules = list(backbone.children())[:-2] # up to conv5_x (feature map) encoder = nn.Sequential(*modules) # output shape: (B, 2048, H/32, W/32) return encoder
Here is an example code snippet that demonstrates how to use the gpen-bfr-2048.pth model to generate an image: gpen-bfr-2048.pth
The "gpen-bfr-2048.pth" file appears to be a pre-trained PyTorch model checkpoint, potentially used for face reconstruction or generation tasks. While we could not find explicit information about this specific file, our analysis suggests that it might be related to a generative patch embedding network (GPEN) architecture. The model could have various applications in image synthesis, face generation, and face reconstruction. def get_encoder(): backbone = models
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