Map-Det3D: Metric Feed-Forward 3D Reconstruction Prior for Multi-view 3D Object Detection from Streaming Inputs
Paper • 2608.12179 • Published
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],
)