Skip to content
Search models or paste a model link. Press Enter to search.

fundamentalvision/BEVFormer

BEVFormer-base architecture graph
BEVFormer-base architecture graph
  • fundamentalvision/BEVFormer
  • INT8
  • AGX Orin
Labels
  • Image
  • Detection
Build
Embedl-optimized
Precision
INT8
Runtime
TensorRT 8.5.1.7 with BEVFormer_tensorrt plugins and Embedl optimizations
Cameras
6 views, 1600×928 each
BEV grid
200×200
Run fundamentalvision/BEVFormer on AGX Orin

BEVFormer-base (R101-DCN backbone) detects 3D objects in the ten nuScenes classes from six surround-view cameras.

BEVFormer is by Zhiqi Li et al. (arXiv:2203.17270), Apache-2.0, at fundamentalvision/BEVFormer; the TensorRT export and plugins are from DerryHub/BEVFormer_tensorrt, Apache-2.0.

Methodology

  • Latency: trtexec GPU compute time of the TensorRT 8.5.1.7 INT8 engine on the Jetson AGX Orin, batch 1, one nuScenes sample (six cameras); mean, p99 and throughput from the same run.
  • Accuracy: NDS and mAP on the 6,019-sample nuScenes validation set, evaluated in PyTorch FP16 with INT8 fake quantization on an NVIDIA L4 with BEVFormer_tensorrt’s bevformer_base_trt_p_q config, not on the device engine. The BEVFormer model zoo’s numbers are shown beside it.
  • Build: exported to ONNX with DerryHub/BEVFormer_tensorrt and compiled on the device with trtexec --fp16 --int8 and its plugin library, which the runtime image carries.
  • Baseline TensorRT: the FP16 build of the same model on TensorRT 8.5.1.7 with the BEVFormer_tensorrt plugins, same device, same trtexec measurement.

Files

Artifacts

What ships in the model bundle.

File Kind Size sha256
TensorRT engine

engine/bevformer_base_trt_p_ptq_max_cp_trtexec.engine

Engine 119.6 MiB 37c54467f693
trtexec build log

logs/trtexec_build.log

Log 14.7 MiB 550d54a52b16
HTTP server for the engine (serve.sh --port 8000)

engine/serve.sh

script 2 KiB c59eaebcab93
Model settings

bevformer.json

Config 394 B 28690ebb2cd9
Latency (trtexec)

benchmark/metrics.json

Results 4 KiB d075ca1389df
Accuracy (PyTorch, on the host)

benchmark/accuracy.json

Results 345 B 82746345f6a9
nuScenes sample (engine inputs, .npz)

inference/nuscenes_sample.npz

sample 141.0 MiB 2eee86c41ff9
Detections for the sample

inference/detections.json

Results 110 KiB 9152f3c6431a
BEVFormer_tensorrt licence

LICENSE-BEVFormer_tensorrt

license 11 KiB c71d239df917

Variants

Every build of fundamentalvision/BEVFormer on AGX Orin.

Variant Precision Speed Runtime

fp16

FP16 1150.31 ms
Latency: GPU compute, mean
TensorRT 8.5.1.7 with BEVFormer_tensorrt plugins
bevformer.orin.runtime.arm64.202610130739ec55

int8

INT8 1143.06 ms
Latency: GPU compute, mean
TensorRT 8.5.1.7 with BEVFormer_tensorrt plugins and Embedl optimizations
bevformer.orin.runtime.arm64.202610130739ec55