DroneStalker-LSTM-0.3

import torch

# Load the model
model = torch.hub.load_state_dict_from_url(
    'https://huggingface.co/Ecoaetix/DroneStalker-LSTM-0.3/resolve/main/drone_stalker-0.3.pth'
)

# Or download and load manually
from huggingface_hub import hf_hub_download

model_path = hf_hub_download(
    repo_id="Ecoaetix/DroneStalker-LSTM-0.3",
    filename="drone_stalker-0.3.pth"
)

# You'll need the Model class (included as model.py in this repo)
from model import Model

model = Model(Np=12, Nf=12, hidden_dim=16, num_layers=1, dropout=0)
model.load_state_dict(torch.load(model_path))
model.eval()

# Inference
with torch.no_grad():
    # Input: [batch_size, 12, 4] - 12 past bounding boxes [x1, y1, x2, y2]
    predictions = model(past_bboxes)
    # Output: [batch_size, 12, 4] - 12 future bounding boxes (min-max normalized)