Bowerbird_individual_ID_classifier

Bowerbird Individual Classifier (ResNet50)

This repository contains the weights for a ResNet50-based individual ID classifier trained on a set of Spotted Bowerbird individuals, as part of a project of the Fusani Lab (see https://github.com/sarequi/Bowerbird-ID).

• Base model: torchvision.models.resnet50 with ResNet50_Weights.DEFAULT (ImageNet)
• Input size: 512 × 512 RGB
• Normalization:
  • mean = [0.485, 0.456, 0.406]
  • std = [0.229, 0.224, 0.225]
• Checkpoint file: Bbird_individual_classifier.pth

This model is not generic. It is specific to the 16 individuals it was trained on. NUM_CLASSES must match the number of bird IDs used during training, unless the model is re-trained.

Usage

import torch
from torchvision.models import resnet50, ResNet50_Weights
from huggingface_hub import hf_hub_download

repo_id = "sarequi/bowerbird-individual-classifier"

# Download checkpoint
ckpt_path = hf_hub_download(
    repo_id=repo_id,
    filename="Bbird_individual_classifier.pth",
)

NUM_CLASSES = 16  # number of individuals used during training

# Rebuild model architecture
model = resnet50(weights=ResNet50_Weights.DEFAULT)
num_ftrs = model.fc.in_features
model.fc = torch.nn.Linear(num_ftrs, NUM_CLASSES)

# Load weights
state_dict = torch.load(ckpt_path, map_location="cpu")
model.load_state_dict(state_dict)
model.eval()