README.md

metadata

tags:
  - pytorch
  - vision
  - face-analysis
  - beauty-prediction
  - scut-fbp5500
library_name: generic
license: mit

SCUT-FBP5500 ResNet-18 Model

This repository contains the PyTorch weights for a facial beauty prediction model trained on the SCUT-FBP5500 dataset.

Model Files

• resnet18.pth: Original weights (saved in Python 2). Requires encoding='latin1' to load in Python 3.
• resnet18_py3.pth: Converted weights compatible with Python 3+ (Recommended).

Model Details

• Architecture: ResNet-18
• Dataset: SCUT-FBP5500 (Facial Beauty Prediction)
• Framework: PyTorch

Origin

The original weights were provided by brian-xu. The resnet18_py3.pth file is a converted version using _use_new_zipfile_serialization=True.

Usage (Python 3)

import torch
import torchvision.models as models

model = models.resnet18(num_classes=1) 

# Load the converted weights (Recommended)
state_dict = torch.load("resnet18_py3.pth")
model.load_state_dict(state_dict)
model.eval()

Licensing

Please refer to the original SCUT-FBP5500 Database for usage terms regarding the dataset and derived models.