This model has been pushed to the Hub using the PytorchModelHubMixin integration:

Usage:

import torch

from mapdet3d.model.mapdet3d import MapDet3D
from mapdet3d.op.mapdet3d.head import RoI2Det

device = "cuda" if torch.cuda.is_available() else "cpu"

# TF32
torch.backends.cuda.matmul.allow_tf32 = True
torch.backends.cudnn.allow_tf32 = True

torch.set_float32_matmul_precision("highest")

# Init model
model = MapDet3D.from_pretrained("RoyYang0714/Map-Det3D").to(device)

# (Optional) Enable tracking
model.track_whole_scene = True
model.roi2det = RoI2Det(nms=True, score_threshold=0.25, iou_threshold=0.5)

# Inference
model.eval()

with torch.no_grad():

with torch.autocast("cuda", enabled=True, dtype=torch.bfloat16):
    predictions: MapDet3DOut = model(
        images=[image],
        intrinsics=[intrinsics],
        extrinsics=[extrinsics],
        frame_ids=[frame_id],
    )
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